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1
Peel, Vincent Robert. "Robust methods for robust passive sonar". Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305876.
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Einicke, Garry A. "Robust filtering /". Title page, contents and introduction only, 1995. http://web4.library.adelaide.edu.au/theses/09PH/09phe35.pdf.
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Ferry, G. "Robust discrimination". Thesis, University of Newcastle Upon Tyne, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239717.
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Sim, Melvyn 1971. "Robust optimization". Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/17725.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.Includes bibliographical references (p. 169-171).
We propose new methodologies in robust optimization that promise greater tractability, both theoretically and practically than the classical robust framework. We cover a broad range of mathematical optimization problems, including linear optimization (LP), quadratic constrained quadratic optimization (QCQP), general conic optimization including second order cone programming (SOCP) and semidefinite optimization (SDP), mixed integer optimization (MIP), network flows and 0 - 1 discrete optimization. Our approach allows the modeler to vary the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations, while keeping the problem tractable. Specifically, for LP, MIP, SOCP, SDP, our approaches retain the same complexity class as the original model. The robust QCQP becomes a SOCP, which is computationally as attractive as the nominal problem. In network flows, we propose an algorithm for solving the robust minimum cost flow problem in polynomial number of nominal minimum cost flow problems in a modified network. For 0 - 1 discrete optimization problem with cost uncertainty, the robust counterpart of a polynomially solvable 0 - 1 discrete optimization problem remains polynomially solvable and the robust counterpart of an NP-hard o-approximable 0-1 discrete optimization problem, remains a-approximable.
(cont.) Under an ellipsoidal uncertainty set, we show that the robust problem retains the complexity of the nominal problem when the data is uncorrelated and identically distributed. For uncorrelated, but not identically distributed data, we propose an approximation method that solves the robust problem within arbitrary accuracy. We also propose a Frank-Wolfe type algorithm for this case, which we prove converges to a locally optimal solution, and in computational experiments is remarkably effective.
by Melvyn Sim.
Ph.D.
5
Öhrström, Albin, e Jubran Muhsin Fadhil. "Robust sköljtank". Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20078.
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Detta arbete behandlar framtagning av en robust sköljtank till en diskmaskin för grovdisk. Sköljtanken har en viktig roll i diskprocessen med ansvarar för att säkerställa att eventuella bakterier, diskmedel och matrester rensas i slutprocessen av diskningen. Därför ställs krav på produkten genom olika standarder för att vara godkänd för användning i diskmaskinen. Kraven berör främst vattentemperaturen samt dimensioner på ett bräddavlopp, som förhindrar att vatten från sköljtanken återströmmas till inloppsvattnet. Syftet med arbetet är att eliminera problem med överhettade värmeelment, opålitliga nivåvakter och korrosion som finns i befintlig sköljtank. Detta uppnås med framtagning av ett nytt sköljtanksystem genom en systematisk produktutvecklingsmetodik som inkluderar tillverkningsanpassad konstruktion (DFM) och miljöanpassad design (DFE). Arbetet resulterar i ett nytt system för sköljtanken med ett ovalformat tvärsnitt och beröringsfria nivåvakter. Detta nya system har ett värmeelement som alltid är täckt med vatten, ger tillförlitlig nivåmätning samt god härdighet mot korrosion. Andra viktiga förbättringar är lägre totalkostnad samt en miljöanpassad design. Det nya sköljtanksystemet lever upp till uppställda krav.This paper is focusing on the development of a robust rinse tank in a dishwashing machine made for pot washing. The rinse tank plays an important role in the dishwashing process, that is to eliminate any bacteria, dish soap or left-overs, in the last step in the finishing process. Therefore demands on the product is set up, based on the required standards. The demands moststly affect the temperature of the water and the dimensions of an overflow, that will prevent the water from flowing back into the supply water pipelines. The purpose of this paper is to eliminate the problems that occur in the existing rinse tank, such as overheated heat element, unreliable level indicators and corrosion. To achieve this, a new robust rinse tank system is developted, by using an systematic product development method that includes design for manufacturing (DFM) and design for environment (DFE). The work results in a new system for the rinse tank, with a oval-shaped cross-section and contactless level sensors. This new system has a heat element that always is underwater, gives a reliable level indication and has a good resistance against corrosion. Other important improvements are a lower total cost together with a environmental design. The new rinse tank system satisfies the set demands.
6
Rix, Andrew Iain James. "Robust rotordynamics". Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/38502/.
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Vibration generated from main rotor unbalance has a major impact on the aerospace gas turbine industry. A combination of logistical and technological drivers differentiate aerospace gas turbines and their derivatives from other types of gas turbines with respect to the approach for managing vibration, leading to a bespoke approach for the design, build, and balancing. The key drivers are: limited accessibility to rotors within the engine, the requirement for exchangeable modules (sub-assemblies) of major parts of the rotor without rebalancing, the use of only low-speed balancing on pseudo-rigid rotors with bladed assemblies, very low vibration limits leading to very tight balancing limits, extreme weight limits for design solutions, and the need for highly accurate, repeatable, and stable rotor joints. This study proposes and demonstrates a novel and rapid robust design system that has been created to deal with these unique challenges. The system comprises an overarching process and a set of novel tools and methods that have been created to support the process. These tools comprise an Unbalance Response Function (URF) design method that effectively delivers a preliminary design assessment and a fast Monte-Carlo simulation and comparison method with supporting software for comparing and improving build and balance design solutions. The aim of the overall process is to generate a system that identifies and controls critical parameters, and alleviates time wasted controlling non-critical parameters. The target outcome is therefore the most cost effective, predictable and repeatable solution with respect to rotor generated vibration (i.e. robust). Two novel methods of informing and improving the outcome of the low-speed balancing process using extra information available about the rotor are also introduced.
7
Anderson, Cynthia 1962. "A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis". Thesis, University of North Texas, 2001. https://digital.library.unt.edu/ark:/67531/metadc5808/.
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A Monte Carlo simulation was used to generate data for a comparison of five robust regression estimation methods with ordinary least squares (OLS) under 36 different outlier data configurations. Two of the robust estimators, Least Absolute Value (LAV) estimation and MM estimation, are commercially available. Three authormodified variations on MM were also included (MM1, MM2, and MM3). Design parameters that were varied include sample size (n=60 and n=180), number of independent predictor variables (2, 3 and 6), outlier density (0%, 5% and 15%) and outlier location (2x,2y s, 8x8y s, 4x,8y s and 8x,4y s). Criteria on which the regression methods were measured are relative efficiency, bias and a test of the null hypothesis. Results indicated that MM2 was the best performing robust estimator on relative efficiency. The best performing estimator on bias was MM1. The best performing regression method on the test of the null hypothesis was MM2. Overall, the MM-type robust regression methods outperformed OLS and LAV on relative efficiency, bias, and the test of the null hypothesis.
8
Lin, Jong-Lick. "Control system design for robust stability and robust performance". Thesis, University of Leicester, 1992. http://hdl.handle.net/2381/34797.
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A central problem in control system design is how to design a controller to guarantee that the closed-loop system is robustly stable and that performance requirements are satisfied despite the presence of model uncertainties and exogenous disturbance signals. The analysis problem, that is the assessment of control systems with respect to robust stability and robust performance, can be adequately solved using the structured singular value u as introduced by Doyle. The corresponding design problem (how to choose a controller K to minimize u) is still largely unsolved, but an approximate solution can be found using Doyle's D - K iteration. In this thesis we present an alternative algorithm, called u - K iteration, which works by flattening the structured singular value u over frequency. As a prelude to this a classical loop shaping approach to robust performance is presented for SISO systems, and is also based on flattening u. In u-synthesis it is often the case that real uncertainties are modelled as complex perturbations but the conservatism so introduced can be severe. On the other hand, if real uncertainties are modelled as real perturbations then D - K iteration is not relevant. It is shown that u - K iteration still works for real perturbations. In addition, a geometric approach for computing the structured singular value for a scalar problem with respect to real and/or complex uncertainty is described. This provides insight into the relationship between real u and complex u. A robust performance problem is considered for a 2-input 2-output high purity distillation column which is an ill-conditioned plant. Analysis reveals the potentially damaging effects on robustness of ill-conditioning. A design is carried out using u - K iteration and the "optimum" u compared with that obtained by Doyle and by Freudenberg for the same problem.
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Gupta, Pramod. "Robust clustering algorithms". Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39553.
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One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across any different fields ranging from computational biology to social sciences to computer vision in part because they are simple and their output is easy to interpret. However, many of these algorithms lack any performance guarantees when the data is noisy, incomplete or has outliers, which is the case for most real world data. It is well known that standard linkage algorithms perform extremely poorly in presence of noise. In this work we propose two new robust algorithms for bottom-up agglomerative clustering and give formal theoretical guarantees for their robustness. We show that our algorithms can be used to cluster accurately in cases where the data satisfies a number of natural properties and where the traditional agglomerative algorithms fail. We also extend our algorithms to an inductive setting with similar guarantees, in which we randomly choose a small subset of points from a much larger instance space and generate a hierarchy over this sample and then insert the rest of the points to it to generate a hierarchy over the entire instance space. We then do a systematic experimental analysis of various linkage algorithms and compare their performance on a variety of real world data sets and show that our algorithms do much better at handling various forms of noise as compared to other hierarchical algorithms in the presence of noise.
10
Cetinyurek, Aysun. "Robust Control Charts". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/3/12607987/index.pdf.
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ABSTRACT
ROBUST CONTROL CHARTS
Çetinyü
rek, Aysun M. Sc., Department of Statistics Supervisor: Dr. BariS Sü
rü
cü
Co-Supervisor: Assoc. Prof. Dr. Birdal Senoglu December 2006, 82 pages Control charts are one of the most commonly used tools in statistical process control. A prominent feature of the statistical process control is the Shewhart control chart that depends on the assumption of normality. However, violations of underlying normality assumption are common in practice. For this reason, control charts for symmetric distributions for both long- and short-tailed distributions are constructed by using least squares estimators and the robust estimators -modified maximum likelihood, trim, MAD and wave. In order to evaluate the performance of the charts under the assumed distribution and investigate robustness properties, the probability of plotting outside the control limits is calculated via Monte Carlo simulation technique.
11
Fu, Ye. "Robust adaptive control". Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/30574.
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This thesis describes discrete robust adaptive control methods based on using slow sampling and slow adaptation. For the stability analysis, we consider that the plant model order is not exactly known and assume that the estimation model order is lower than the plant model order. A stability condition is derived with a given upper limit for the adaptation gain which is related to a strictly positive real operator. Discussion of the relation between sampling and stability condition is then given. For the robust adaptive control design, we study slow adaptation and predictive control. For the slow adaptation, the main idea is to use only good estimates and use a compensation filter. Some frequency domain information on the plant is necessary for this method. For predictive control, we discuss the relationship between the extended control horizon and the critical sampling. For a simple case, it is shown that the larger extended control horizon brings more robust adaptive control.
The purpose of this thesis is to provide robust discrete adaptive controller design guidelines, especially in such cases as using slow sampling frequency, slow adaptation rate. It is true that in practice, for various discrete adaptive control algorithms, slow sampling and slow adaptation rate will bring more robustness. The use of slow sampling and slow adaptation rate is simple and economic, thus a careful choice of sampling rate and adaptation rate is highly recommended. This thesis provides such guidelines for choosing proper sampling rate and adaptation rate for robust discrete adaptive control.Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
12
Schumann, David Heinz. "Robust Variable Selection". NCSU, 2009. http://www.lib.ncsu.edu/theses/available/etd-03262009-153524/.
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The prevalence of extreme outliers in many regression data sets has led to the development of robust methods that can handle these observations. While much attention has been placed on the problem of estimating regression coefficients in the presence of outliers, few methods address variable selection. We develop and study robust versions of the forward selection algorithm, one of the most popular standard variable selection techniques. Specifically we modify the VAMS procedure, a version of forward selection tuned to control the false selection rate, to simultaneously select variables and eliminate outliers. In an alternative approach, robust versions of the forward selection algorithm are developed using the robust forward addition sequence associated with the generalized score statistic. Combining the robust forward addition sequence with robust versions of BIC and the VAMS procedure, a final model is obtained. Monte Carlo simulation compares these robust methods to current robust methods like the LSA and LAD-LASSO. Further simulation investigates the relationship between the breakdown point of the estimation methods central to each procedure and the breakdown point of the final variable selection method.
13
Olver, Neil. "Robust network design". Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=95085.
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Robust network design takes the very successful framework of robust optimization and applies it to the area of network design, motivated by applications in communication networks. The main premise is that demands across the network are not fixed, but are variable or uncertain. However, they are known to fall within a prescribed uncertainty set. Our solution must have sufficient capacity to route any demand in this set; moreover, the routing must be oblivious, meaning it must be fixed up front, and not depend on the particular choice of demand from within the uncertainty set. A particular choice of uncertainty set within this framework yields the "hose model", which has received particular attention due to applications to virtual private networks. A 2-approximation was known for the problem, using a solution template in the form of a tree. It was conjectured that this tree solution is actually always optimal; this became known as the "VPN Conjecture". As one of the central results of this thesis, we prove this conjecture in full generality. In addition, we demonstrate a counterexample to a stronger multipath (fractional routing) version of the conjecture which had also been proposed. We initiate a study of the robust network design problem more generally, with a focus on approximability. In the general model, where the uncertainty set is given by an arbitrary separable polyhedron, we give a strong inapproximability result. We then consider a new and natural model generalizing the symmetric hose model, based on demands routable on a given tree, and provide a constant factor approximation algorithm. Lastly, we compare oblivious routing with the much more flexible (but also less practical) dynamic routing scheme where the routing may vary depending on the demand pattern. We show that in the worst case, the cost of an optimal oblivious routing solution can be much more expensive than the dynamic optimum, by up to a logarithmic factor.Motivé par les applications concernantes les réseaux de communication, le dessein des réseaux robustes applique les méthodes très réusies provenant de l'optimisation robuste. La prémisse principale est que les demandes sur le réseau ne sont pas fixes, mais variables ou incertaines. Cependant, nous savons qu'elles sont tirées d'un ensemble d'incertitude prescrit. Il faut que la solution ait une capacité suffisante pour pouvoir router toute demande appartenant à cet ensemble. En outre, il faut que le routage soit oublieux, ce qui signifie qu'il peut être fixé à l'avance, et ne dépends pas du choix particulier de la demande appartenant de l'ensemble d'incertitude. Dans ce cadre, il existe un choix particulier d'ensemble d'incertitude qui mène au « modèle de tuyau ». Ce modèle a reçu une attention particulière à causede ses applications aux réseaux privés virtuels. On connaissait un 2-rapprochement utilisant une solution en forme d'arbre. La « Conjecture de VPN » énonce que cette solution en forme d'arbre est toujours optimale. L'un des résultats principaux de cette thèse démontre cette conjecture en toute généralité. En outre, nous donnons un contre-exemple à une version plus forte de la conjecture concernant les chemins multiples (le routage étant fractionnel) qui avait également été proposée. Nous initions l'étude du problème de la conception de réseaux robustes dans une plus grande généralité, en insistant sur l'approximabilité. Dans le modèle général, où l'ensemble d'incertitude est un polyèdre séparable arbitraire, nous donnons un résultat fort d'inapproximabilité. Nous considérons ensuite un nouveau modèle naturel généralisant le modèle de tuyau symétrique, qui est basé sur des demandes qui peuvent être routées sur un arbre donné, et nous fournissons un algorithme ayant un facteur de rapprochement constant. Finalement, nous comparons le routage oublieux avec le schéma beaucoup plus flexible (
14
Foisy, André. "Robust collision detection". Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=28746.
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The problem of locating collisions between computer modeled moving rigid bodies is considered. Each rigid body is modeled by the union of polytopes. Safe and reliable collision detection algorithms are constructed.Since the computer representation of real numbers is finite, an interval projective point is used to encompass all localization errors of a modeled point. An interval point is the elementary geometrical form from which all others are constructed. The Euclidean convex set spanned by an interval point is also a polytope.
The construction of a polytope relies on a robust convex hull algorithm. The computed hull is guaranteed to contain all interval projective points.
An extrusion based collision detection algorithm builds an AND-OR decision tree. Each leaf is a univariate function that expresses the relation between a moving point and a moving plane. Interval zero finding methods are applied to find the overlap and non-overlap portions of the trajectories of moving polytopes.
The swept-volume based collision detection algorithm depends on the construction of a convex approximation that comprises the real swept volume. To obtain a convex approximation, the convex hull algorithm is applied to the bounding volumes of the vertices of a moving polytope. Each bounding volume is an interval projective point.
Finally, both collision detection algorithms are tested in the context of generate-and-test path planning.
15
Anderson, Ross John. "Robust computer security". Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338198.
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Cheng, You-Chi. "Robust gesture recognition". Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53492.
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It is a challenging problem to make a general hand gesture recognition system work in a practical operation environment. In this study, it is mainly focused on recognizing English letters and digits performed near the steering wheel of a car and captured by a video camera. Like most human computer interaction (HCI) scenarios, the in-car gesture recognition suffers from various robustness issues, including multiple human factors and highly varying lighting conditions. It therefore brings up quite a few research issues to be addressed. First, multiple gesturing alternatives may share the same meaning, which is not typical in most previous systems. Next, gestures may not be the same as expected because users cannot see what exactly has been written, which increases the gesture diversity significantly.In addition, varying illumination conditions will make hand detection trivial and thus result in noisy hand gestures. And most severely, users will tend to perform letters at a fast pace, which may result in lack of frames for well-describing gestures. Since users are allowed to perform gestures in free-style, multiple alternatives and variations should be considered while modeling gestures. The main contribution of this work is to analyze and address these challenging issues step-by-step such that eventually the robustness of the whole system can be effectively improved. By choosing color-space representation and performing the compensation techniques for varying recording conditions, the hand detection performance for multiple illumination conditions is first enhanced. Furthermore, the issues of low frame rate and different gesturing tempo will be separately resolved via the cubic B-spline interpolation and i-vector method for feature extraction. Finally, remaining issues will be handled by other modeling techniques such as sub-letter stroke modeling. According to experimental results based on the above strategies, the proposed framework clearly improved the system robustness and thus encouraged the future research direction on exploring more discriminative features and modeling techniques.
17
Pearce, Kim Frances. "Robust logistic discrimination". Thesis, University of Newcastle Upon Tyne, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294687.
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REYNA, FERNANDO ROLFI QUINECHE. "ROBUST OPTIMAL PORTFOLIO". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2001. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=1938@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOOs mercados de ações dos países emergentes tem como principal característica a presença de dias atípicos, os quais fazem impossível o uso, com sucesso, dos modelos de equilíbrio. O principal objetivo desta pesquisa é a de desenvolver uma nova teoria, baseada na estatísica robusta, que possa ser aplicada a estes mercados sem ser seriamente afetada por observações extremas, e que ao mesmo tempo, ofereça resultados eficientes e precisos.
Emergent stock markets are characterized by the presence of atypical days, which make impossible the use of equilibrium models with sucess. The main aim of this research is to define a new theory, based on the robust statistical theory, which could be applied to those markets without being affected by extreme observations and, at the same time, offer efficient and accurate results.
Los mercados de acciones de los países emergentes tienen como principal característica la presencia de días atípicos, lo que hace imposible el uso, con suceso, de los modelos de equilibrio. EL objetivo principal de esta investigación es desarrollar una nueva teoría, basada en la estadística robusta, que pueda ser aplicada a estos mercados sin ser seriamente afectada por observaciones extremas, y que al mismo tiempo, obtenga resultados eficientes y precisos.
19
Barr, Mohammad. "Robust logo watermarking". Thesis, De Montfort University, 2018. http://hdl.handle.net/2086/16550.
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Digital image watermarking is used to protect the copyright of digital images. In this thesis, a novel blind logo image watermarking technique for RGB images is proposed. The proposed technique exploits the error correction capabilities of the Human Visual System (HVS). It embeds two different watermarks in the wavelet/multiwavelet domains. The two watermarks are embedded in different sub-bands, are orthogonal, and serve different purposes. One is a high capacity multi-bit watermark used to embed the logo, and the other is a 1-bit watermark which is used for the detection and reversal of geometrical attacks. The two watermarks are both embedded using a spread spectrum approach, based on a pseudo-random noise (PN) sequence and a unique secret key. Robustness against geometric attacks such as Rotation, Scaling, and Translation (RST) is achieved by embedding the 1-bit watermark in the Wavelet Transform Modulus Maxima (WTMM) coefficients of the wavelet transform. Unlike normal wavelet coefficients, WTMM coefficients are shift invariant, and this important property is used to facilitate the detection and reversal of RST attacks. The experimental results show that the proposed watermarking technique has better distortion parameter detection capabilities, and compares favourably against existing techniques in terms of robustness against geometrical attacks such as rotation, scaling, and translation.
20
Zhou, Chong. "Robust Auto-encoders". Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-theses/393.
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In this thesis, our aim is to improve deep auto-encoders, an important topic in the deep learning area, which has shown connections to latent feature discovery models in the literature. Our model is inspired by robust principal component analysis, and we build an outlier filter on the top of basic deep auto-encoders. By adding this filter, we can split the input data X into two parts X=L+S, where the L could be better reconstructed by a deep auto-encoder and the S contains the anomalous parts of the original data X. Filtering out the anomalies increases the robustness of the standard auto-encoder, and thus we name our model ``Robust Auto-encoder'. We also propose a novel solver for the robust auto-encoder which alternatively optimizes the reconstruction cost of the deep auto-encoder and the sparsity of outlier filter in pursuit of finding the optimal solution. This solver is inspired by the Alternating Direction Method of Multipliers, Back-propagation and the Alternating Projection method, and we demonstrate the convergence properties of this algorithm and its superior performance in standard image recognition tasks. Last but not least, we apply our model to multiple domains, especially, the cyber-data analysis, where deep models are seldom currently used.
21
Chua, Shui Ying. "Robust network design". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99030.
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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT.Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 61-63).
As an equipment manufacturer for the mining and construction industries, Caterpillar's business is heavily impacted by the cyclicality of these two industries. To be competitive in the market while investing prudently to ensure shareholders' value, Caterpillar needs to make capacity decisions with peaks and troughs of the cycles in mind. Through the peaks and troughs of business cycles, the perceptions change from not enough capacity to under-utilization of asset constrained capacity respectively. The purpose of this thesis is to establish a framework that enhances robustness in investment decision-making within the 2-6 year capacity planning horizon. This entails the ability to balance risk and return for the company and account for the cyclical nature of business and other strategic considerations. The project also aims to enhance consistency across stakeholders and introduce an aggregate risk perspective under corporate capital constraint.
by Shui Ying Chua.
M.B.A.
S.M.
22
Teo, Kwong Meng. "Nonconvex robust optimization". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40303.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 133-138).
We propose a novel robust optimization technique, which is applicable to nonconvex and simulation-based problems. Robust optimization finds decisions with the best worst-case performance under uncertainty. If constraints are present, decisions should also be feasible under perturbations. In the real-world, many problems are nonconvex and involve computer-based simulations. In these applications, the relationship between decision and outcome is not defined through algebraic functions. Instead, that relationship is embedded within complex numerical models. Since current robust optimization methods are limited to explicitly given convex problems, they cannot be applied to many practical problems. Our proposed method, however, operates on arbitrary objective functions. Thus, it is generic and applicable to most real-world problems. It iteratively moves along descent directions for the robust problem, and terminates at a robust local minimum. Because the concepts of descent directions and local minima form the building blocks of powerful optimization techniques, our proposed framework shares the same potential, but for the richer, and more realistic, robust problem.
(cont.) To admit additional considerations including parameter uncertainties and nonconvex constraints, we generalized the basic robust local search. In each case, only minor modifications are required - a testimony to the generic nature of the method, and its potential to be a component of future robust optimization techniques. We demonstrated the practicability of the robust local search technique in two realworld applications: nanophotonic design and Intensity Modulated Radiation Therapy (IMRT) for cancer treatment. In both cases, the numerical models are verified by actual experiments. The method significantly improved the robustness for both designs, showcasing the relevance of robust optimization to real-world problems.
by Kwong Meng Teo.
Ph.D.
23
Hsiao, Kaijen. "Relatively robust grasping". Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/55115.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 135-138).
This thesis presents an approach for grasping objects robustly under significant positional uncertainty. In the field of robot manipulation there has been a great deal of work on how to grasp objects stably, and in the field of robot motion planning there has been a great deal of work on how to find collision-free paths to those grasp positions. However, most of this work assumes exact knowledge of the shapes and positions of both the object and the robot; little work has been done on how to grasp objects robustly in the presence of position uncertainty. To reason explicitly about uncertainty while grasping, we model the problem as a partially observable Markov decision process (POMDP). We derive a closed-loop strategy that maintains a belief state (a probability distribution over world states), and select actions with a receding horizon using forward search through the belief space. Our actions are world-relative trajectories (WRT): fixed trajectories expressed relative to the most-likely state of the world. We localize the object, ensure its reachability, and robustly grasp it at a specified position by using information-gathering, reorientation, and goal-seeking WRT actions. This framework is used to grasp objects (including a power drill and a Brita pitcher) despite significant uncertainty, using a 7-DOF Barrett Arm and attached 4-DOF Barrett Hand equipped with force and contact sensors. Our approach is generalizable to almost any sensor type, as well as wide ranges of sensor error and pose uncertainty.
by Kaijen Hsiao.
Ph.D.
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Pritchard, David (David Alexander Griffith). "Robust network computation". Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/37069.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 91-98).
In this thesis, we present various models of distributed computation and algorithms for these models. The underlying theme is to come up with fast algorithms that can tolerate faults in the underlying network. We begin with the classical message-passing model of computation, surveying many known results. We give a new, universally optimal, edge-biconnectivity algorithm for the classical model. We also give a near-optimal sub-linear algorithm for identifying bridges, when all nodes are activated simultaneously. After discussing some ways in which the classical model is unrealistic, we survey known techniques for adapting the classical model to the real world. We describe a new balancing model of computation. The intent is that algorithms in this model should be automatically fault-tolerant. Existing algorithms that can be expressed in this model are discussed, including ones for clustering, maximum flow, and synchronization. We discuss the use of agents in our model, and give new agent-based algorithms for census and biconnectivity. Inspired by the balancing model, we look at two problems in more depth.
(cont.) First, we give matching upper and lower bounds on the time complexity of the census algorithm, and we show how the census algorithm can be used to name nodes uniquely in a faulty network. Second, we consider using discrete harmonic functions as a computational tool. These functions are a natural exemplar of the balancing model. We prove new results concerning the stability and convergence of discrete harmonic functions, and describe a method which we call Eulerization for speeding up convergence.
by David Pritchard.
M.Eng.
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Yu, Chun. "Robust mixture modeling". Diss., Kansas State University, 2014. http://hdl.handle.net/2097/18153.
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Doctor of PhilosophyDepartment of Statistics
Weixin Yao and Kun Chen
Ordinary least-squares (OLS) estimators for a linear model are very sensitive to unusual values in the design space or outliers among y values. Even one single atypical value may have a large effect on the parameter estimates. In this proposal, we first review and describe some available and popular robust techniques, including some recent developed ones, and compare them in terms of breakdown point and efficiency. In addition, we also use a simulation study and a real data application to compare the performance of existing robust methods under different scenarios. Finite mixture models are widely applied in a variety of random phenomena. However, inference of mixture models is a challenging work when the outliers exist in the data. The traditional maximum likelihood estimator (MLE) is sensitive to outliers. In this proposal, we propose a Robust Mixture via Mean shift penalization (RMM) in mixture models and Robust Mixture Regression via Mean shift penalization (RMRM) in mixture regression, to achieve simultaneous outlier detection and parameter estimation. A mean shift parameter is added to the mixture models, and penalized by a nonconvex penalty function. With this model setting, we develop an iterative thresholding embedded EM algorithm to maximize the penalized objective function. Comparing with other existing robust methods, the proposed methods show outstanding performance in both identifying outliers and estimating the parameters.
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Bai, Xue. "Robust linear regression". Kansas State University, 2012. http://hdl.handle.net/2097/14977.
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Master of ScienceDepartment of Statistics
Weixin Yao
In practice, when applying a statistical method it often occurs that some observations deviate from the usual model assumptions. Least-squares (LS) estimators are very sensitive to outliers. Even one single atypical value may have a large effect on the regression parameter estimates. The goal of robust regression is to develop methods that are resistant to the possibility that one or several unknown outliers may occur anywhere in the data. In this paper, we review various robust regression methods including: M-estimate, LMS estimate, LTS estimate, S-estimate, [tau]-estimate, MM-estimate, GM-estimate, and REWLS estimate. Finally, we compare these robust estimates based on their robustness and efficiency through a simulation study. A real data set application is also provided to compare the robust estimates with traditional least squares estimator.
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Cardoso, João Nuno Martins. "Robust mean variance". Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/10706.
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Mestrado em FinançasEste estudo empírico tem como objectivo avaliar o impacto da estimação robusta nos portefólios de média variância. Isto foi conseguido fazendo uma simulação do comportamento de 15 acções do SP500. Esta simulação inclui dois cenários: um com amostras que seguem uma distribuição normal e outro com amostras contaminadas não normais. Cada cenário inclui 200 reamostragens. O performance dos portefólios estimados usando a máxima verosimilhança (clássicos) e dos portefólios estimados de forma robusta são comparados, resultando em algumas conclusões: Em amostras normais, portefólios robustos são marginalmente menos eficientes que os portefólios clássicos. Contudo, em amostras não normais, os portefólios robustos apresentam um performance muito superior que os portefólios clássicos. Este acréscimo de performance está positivamente correlacionado com o nível de contaminação da amostra. Em suma, assumindo que os retornos financeiros têm uma distribuição não normal, podemos afirmar que os estimadores robustos resultam em portefólios de média variância mais estáveis.
This empirical study's objective is to evaluate the impact of robust estimation on mean variance portfolios. This was accomplished by doing a simulation on the behavior of 15 SP500 stocks. This simulation includes two scenarios: One with normally distributed samples and another with contaminated non-normal samples. Each scenario includes 200 resamples. The performance of maximum likelihood (classical) estimated portfolios and robustly estimated portfolios are compared, resulting in some conclusions: On normally distributed samples, robust portfolios are marginally less efficient than classical portfolios. However, on non-normal samples, robust portfolios present a much higher performance than classical portfolios. This increase in performance is positively correlated with the level of contamination present on the sample. In summary, assuming that financial returns do not present a normal distribution, we can state that robust estimators result in more stable mean variance portfolios.
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Shen, Dennis Ph D. Massachusetts Institute of Technology. "Robust synthetic control". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115743.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 63-65).
In this thesis, we present a robust generalization of the synthetic control method. A distinguishing feature of our algorithm is that of de-noising the data matrix via singular value thresholding, which renders our approach robust in multiple facets: it automatically identifies a good subset of donors, functions without extraneous covariates (vital to existing methods), and overcomes missing data (never been addressed in prior works). To our knowledge, we provide the first theoretical finite sample analysis for a broader class of models than previously considered in literature. Additionally, we relate the inference quality of our estimator to the amount of training data available and show our estimator to be asymptotically consistent. In order to move beyond point estimates, we introduce a Bayesian framework that not only provides practitioners the ability to readily develop different estimators under various loss functions, but also equips them with the tools to quantitatively measure the uncertainty of their model/estimates through posterior probabilities. Our empirical results demonstrate that our robust generalization yields a positive impact over the classical synthetic control method, underscoring the value of our key de-noising procedure.
by Dennis Shen.
S.M.
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Chen, Ho-Lin. "Robust self-assembly /". May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
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Fischer, Jeffrey M. "Robust service composition". Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1779690531&sid=3&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Knott, Paul Alexander. "Robust quantum metrology". Thesis, University of Leeds, 2015. http://etheses.whiterose.ac.uk/8931/.
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In optical interferometry path-entangled states such as NOON states have shown to give quantum-enhanced precision measurements, but these states are notoriously fragile to particle losses, which typically collapse the quantum state and destroy the phase information. A class of inherently robust states that show the potential for great improvements over the alternatives are the entangled coherent states (ECSs). We show that these states allow substantial improvements over unentangled `classical' states and highly-entangled NOON states for a wide range of loss values. We then describe a measurement scheme that can be used to measure these states with a precision close to the theoretical bound given by the quantum Fisher information. We then look at the quantum mechanisms that lead to precise measurements. In optical interferometry multi-mode entanglement is often assumed to be the driving force behind quantum enhanced measurements. Recent work has shown this assumption to be false, and here we show that when photon losses occur multi-mode entanglement is actually detrimental to obtaining quantum enhanced measurements. We specifically apply this idea to a superposition of coherent states, demonstrating that these states show a robustness to loss that allows them to significantly outperform their competitors in realistic systems. A practically viable measurement scheme is then presented that allows measurements close to the theoretical bound, even with loss. In this thesis we also consider superpositions of spin coherent states and their application to quantum metrology. Compared to optical states, spin systems have a distinctly different process of decoherence known as non-Markovian dephasing, which has shown to give greatly improved robustness to loss. We see that spin cat states give an enhanced scaling over the shot noise limit, even with dephasing, whilst being realisable with current technology.
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Liu, Chengyuan. "Robust model predictive control : robust control invariant sets and efficient implementation". Thesis, Imperial College London, 2017. http://hdl.handle.net/10044/1/45529.
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Robust model predictive control (RMPC) is widely used in industry. However, the online computational burden of this algorithm restricts its development and application to systems with relatively slow dynamics. We investigate this problem in this thesis with the overall aim of reducing the online computational burden and improving the online efficiency. In RMPC schemes, robust control invariant (RCI) sets are vitally important in dealing with constraints and providing stability. They can be used as terminal (invariant) sets in RMPC schemes to reduce the online computational burden and ensure stability simultaneously. To this end, we present a novel algorithm for the computation of full-complexity polytopic RCI sets, and the corresponding feedback control law, for linear discrete-time systems subject to output and initial state constraints, performance bounds, and bounded additive disturbances. Two types of uncertainty, structured norm-bounded and polytopic uncertainty, are considered. These algorithms are then extended to deal with systems subject to asymmetric initial state and output constraints. Furthermore, the concept of RCI sets can be extended to invariant tubes, which are fundamental elements in tube based RMPC scheme. The online computational burden of tube based RMPC schemes is largely reduced to the same level as model predictive control for nominal systems. However, it is important that the constraint tightening that is needed is not excessive, otherwise the performance of the MPC design may deteriorate, and there may even not exist a feasible control law. Here, the algorithms we proposed for RCI set approximations are extended and applied to the problem of reducing the constraint tightening in tube based RMPC schemes. In order to ameliorate the computational complexity of the online RMPC algorithms, we propose an online-offline RMPC method, where a causal state feedback structure on the controller is considered. In order to improve the efficiency of the online computation, we calculate the state feedback gain offline using a semi-definite program (SDP). Then we propose a novel method to compute the control perturbation component online. The online optimization problem is derived using Farkas' Theorem, and then approximated by a quadratic program (QP) to reduce the online computational burden. A further approximation is made to derive a simplified online optimization problem, which results in a large reduction in the number of variables. Numerical examples are provided that demonstrate the advantages of all our proposed algorithms over current schemes.
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Rippel, Markus. "Improved robustness formulations and a simulation-based robust concept exploration method". Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31850.
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Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010.Committee Chair: Allen, Janet K.; Committee Member: Choi, Seung-Kyum; Committee Member: Mistree, Farrokh. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Al-Takrouri, Saleh Othman Saleh Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Robust state estimation and model validation techniques in computer vision". Publisher:University of New South Wales. Electrical Engineering & Telecommunications, 2008. http://handle.unsw.edu.au/1959.4/41002.
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The main objective of this thesis is to apply ideas and techniques from modern control theory, especially from robust state estimation and model validation, to various important problems in computer vision. Robust model validation is used in texture recognition where new approaches for classifying texture samples and segmenting textured images are developed. Also, a new model validation approach to motion primitive recognition is demonstrated by considering the motion segmentation problem for a mobile wheeled robot. A new approach to image inpainting based on robust state estimation is proposed where the implementation presented here concerns with recovering corrupted frames in video sequences. Another application addressed in this thesis based on robust state estimation is video-based tracking. A new tracking system is proposed to follow connected regions in video frames representing the objects in consideration. The system accommodates tracking multiple objects and is designed to be robust towards occlusions. To demonstrate the performance of the proposed solutions, examples are provided where the developed methods are applied to various gray-scale images, colored images, gray-scale videos and colored videos. In addition, a new algorithm is introduced for motion estimation via inverse polynomial interpolation. Motion estimation plays a primary role within the video-based tracking system proposed in this thesis. The proposed motion estimation algorithm is also applied to medical image sequences. Motion estimation results presented in this thesis include pairs of images from a echocardiography video and a robot-assisted surgery video.
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Zhao, Yong. "Nonlinear compensation and heterogeneous data modeling for robust speech recognition". Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47566.
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The goal of robust speech recognition is to maintain satisfactory recognition accuracy under mismatched operating conditions. This dissertation addresses the robustness issue from two directions.
In the first part of the dissertation, we propose the Gauss-Newton method as a unified approach to estimating noise parameters for use in prevalent nonlinear compensation models, such as vector Taylor series (VTS), data-driven parallel model combination (DPMC), and unscented transform (UT), for noise-robust speech recognition. While iterative estimation of noise means in a generalized EM framework has been widely known, we demonstrate that such approaches are variants of the Gauss-Newton method. Furthermore, we propose a novel noise variance estimation algorithm that is consistent with the Gauss-Newton principle. The formulation of the Gauss-Newton method reduces the noise estimation problem to determining the Jacobians of the corrupted speech parameters. For sampling-based compensations, we present two methods, sample Jacobian average (SJA) and cross-covariance (XCOV), to evaluate these Jacobians. The Gauss-Newton method is closely related to another noise estimation approach, which views the model compensation from a generative perspective, giving rise to an EM-based algorithm analogous to the ML estimation for factor analysis (EM-FA). We demonstrate a close connection between these two approaches: they belong to the family of gradient-based methods except with different convergence rates. Note that the convergence property can be crucial to the noise estimation in many applications where model compensation may have to be frequently carried out in changing noisy environments to retain desired performance. Furthermore, several techniques are explored to further improve the nonlinear compensation approaches. To overcome the demand of the clean speech data for training acoustic models, we integrate nonlinear compensation with adaptive training. We also investigate the fast VTS compensation to improve the noise estimation efficiency, and combine the VTS compensation with acoustic echo cancellation (AEC) to mitigate issues due to interfering background speech. The proposed noise estimation algorithm is evaluated for various compensation models on two tasks. The first is to fit a GMM model to artificially corrupted samples, the second is to perform speech recognition on the Aurora 2 database, and the third is on a speech corpus simulating the meeting of multiple competing speakers. The significant performance improvements confirm the efficacy of the Gauss-Newton method to estimating the noise parameters of the nonlinear compensation models.
The second research work is devoted to developing more effective models to take full advantage of heterogeneous speech data, which are typically collected from thousands of speakers in various environments via different transducers. The proposed synchronous HMM, in contrast to the conventional HMMs, introduces an additional layer of substates between the HMM state and the Gaussian component variables. The substates have the capability to register long-span non-phonetic attributes, such as gender, speaker identity, and environmental condition, which are integrally called speech scenes in this study. The hierarchical modeling scheme allows an accurate description of probability distribution of speech units in different speech scenes. To address the data sparsity problem in estimating parameters of multiple speech scene sub-models, a decision-based clustering algorithm is presented to determine the set of speech scenes and to tie the substate parameters, allowing us to achieve an excellent balance between modeling accuracy and robustness. In addition, by exploiting the synchronous relationship among the speech scene sub-models, we propose the multiplex Viterbi algorithm to efficiently decode the synchronous HMM within a search space of the same size as for the standard HMM. The multiplex Viterbi can also be generalized to decode an ensemble of isomorphic HMM sets, a problem often arising in the multi-model systems. The experiments on the Aurora 2 task show that the synchronous HMMs produce a significant improvement in recognition performance over the HMM baseline at the expense of a moderate increase in the memory requirement and computational complexity.
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Smith, Barry Craig. "Robust Airline Fleet Assignment". Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4930.
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Robust Airline Fleet Assignment
Barry C. Smith
140 Pages
Directed by Dr. Ellis L. Johnson
Fleet assignment models are used by many airlines to assign aircraft to flights in a schedule to maximize profit. Major airlines report that the use of fleet assignment models increases annual profits by more than $100 million. The results of fleet assignment models affect subsequent planning, marketing and operational processes within the airline. Anticipating these processes and developing solutions favorable to them can further increase the benefits of fleet assignment models.
We propose to produce fleet assignment solutions that increase planning flexibility and reduce cost by imposing station purity, limiting the number of fleet types allowed to serve each airport in the schedule. We demonstrate that imposing station purity on the fleet assignment model can limit aircraft dispersion in the network and make solutions more robust relative to crew planning, maintenance planning and operations. Because station purity can significantly degrade computational efficiency, we develop a solution approach, Station Decomposition, which takes advantage of airline network structure. Station Decomposition uses a column generation approach to solving the fleet assignment problem; we further improve the performance of Station Decomposition by developing a primal-dual method that increases the solution quality and model efficiency. Station Decomposition solutions can be highly fractional; we develop a fix and price heuristic to efficiently find integer solutions to the fleet assignment problem.
Airline profitability can be increased if fleet assignment models anticipate the effects of marketing processes such as revenue management. We develop an approach, ODFAM, which incorporates airline revenue management effects into the fleet assignment model. We develop an approach to incorporate station purity and ODFAM using a combination of column and cut generation. This approach can increase airline profit up to $27 million per year.
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Balci, Salih Eren. "Robust Watermarking Of Images". Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1091917/index.pdf.
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Digital image watermarking has gained a great interest in the last decade among researchers. Having such a great community which provide a continuously growing list of proposed algorithms, it is rapidly finding solutions to its problems. However, still we are far away from being successful. Therefore, more and more people are entering the field to make the watermarking idea useful and reliable for digital world. Of these various watermarking algorithms, some outperform others in terms of basic watermarking requirements like robustness, invisibility, processing cost, etc.
In this thesis, we study the performances of different watermarking algorithms in terms of robustness. Algorithms are chosen to be representatives of different categories such as spatial and transform domain. We evaluate the performance of a selected set of 9 different methods from the watermarking literature against again a selected set of attacks and distortions and try to figure out the properties of the methods that make them vulnerable or invulnerable against these attacks.
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Tshangini, Mati. "Multicell robust downlink beamforming". Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/multicell-robust-downlink-beamforming(fde2310c-98de-440c-ab32-6a4257489d8c).html.
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The growth in large number of users and data exchange in cellular networks, has led to an urgent improvement of the power efficiency in cellular networks. The capacity and coverage are of main concern due to the fast growing applications and demand in different areas of use. The scarcity of the traditional communications resources like time and spectrum and the safety limits on transmit power from the base stations antennas as well as the mobile terminals demand the use of new additional resources such as spatial dimensions and cooperation for the realisation of the future cellular networks. Different distributively overlaid wireless cellular network systems are being deployed to meet demand for high data rates. However, these distributively overlaid wireless cellular networks can cause higher inter-cell interference if the signals from the source antennas are not combined and coordinated. Therefore, the solution to eliminating interference is considered as the benchmark for reducing the power consumption in the network. This thesis aims to address these concerns by proposing different algorithm techniques based on beamforming for Multi-Cell Processing (MCP) addressed across multiple coordinating multi-antenna base stations. First, a distributed optimization problem in a standard semidefinite relaxation (SDR) is introduced that minimizes a combination of the sum-power, used by each base station (BS) to transmit data to its local users, and the worst-case of the resulting overall interference induced on the other users of the adjacent cells in the presence of imperfect channel state information (CSI). The aim is to ensure that the worst-cases of the signal-to-interference- plus-noise ratio (SINR) at each user remains above the required level. The feasibility solutions are achieved for certain sets of SINRs only due to relaxation of optimal beamforming. To avoid relaxation and achieve higher SINRS, a second-order cone programming (SOCP), is introduced which is solved efficiently and achieve higher SINRs. Not only for its power efficiency improvement, but, also SOCP algorithm reduces the complexity of the extra signalling overhead.
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Kpamegan, Neil Racheed. "Robust Principal Component Analysis". Thesis, American University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10784806.
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In multivariate analysis, principal component analysis is a widely popular method which is used in many different fields. Though it has been extensively shown to work well when data follows multivariate normality, classical PCA suffers when data is heavy-tailed. Using PCA with the assumption that the data follows a stable distribution, we will show through simulations that a new method is better. We show the modified PCA can be used for heavy-tailed data and that we can more accurately estimate the correct number of components compared to classical PCA and more accurately identify the subspace spanned by the important components.
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Nosratighods, Mohaddeseh Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Robust speaker verification system". Publisher:University of New South Wales. Electrical Engineering & Telecommunications, 2008. http://handle.unsw.edu.au/1959.4/42796.
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Identity verification or biometric recognition systems play an important role in our daily lives. Applications include Automatic Teller Machines (ATM), banking and share information retrieval, and personal verification for credit cards. Among the biometric techniques, authentication of speakers by his/her voice is of great importance, since it employs a non-invasive approach and is the only available modality in many applications. However,the performance of Automatic Speaker Verification (ASV) systems degrades significantly under adverse conditions which cause recordings from the same speaker to be different.The objective of this research is to investigate and develop robust techniques for performing automatic speaker recognition over various channel conditions, such as telephony and recorded microphone speech. This research is shown to improve the robustness of ASV systems in three main areas of feature extraction, speaker modelling and score normalization. At the feature level, a new set of dynamic features, termed Delta Cepstral Energy (DCE) is proposed, instead of traditional delta cepstra, which not only greatly reduces thedimensionality of the feature vector compared with delta and delta-delta cepstra, but is also shown to provide the same performance for matched testing and training conditions on TIMIT and a subset of the NIST 2002 dataset. The concept of speaker entropy, which conveys the information contained in a speaker's speech based on the extracted features, facilitates comparative evaluation of the proposed methods. In addition, Frequency Modulation features are combined in a complementary manner with the Mel Frequency CepstralCoefficients (MFCCs) to improve the performance of the ASV system under channel variability of various types. The proposed fused system shows a relative reduction of up to 23% in Equal Error Rate (EER) over the MFCC-based system when evaluated on the NIST 2008 dataset. Currently, the main challenge in speaker modelling is channel variability across different sessions. A recent approach to channel compensation, based on Support Vector Machines (SVM) is Nuisance Attribute Projection (NAP). The proposed multi-component approach to NAP, attempts to compensate for the main sources of inter-session variations through an additional optimization criteria, to allow more accurate estimates of the most dominant channel artefacts and to improve the system performance under mismatched training and test conditions. Another major issue in speaker recognition is that the variability of score distributions due to incompletely modelled regions of the feature space can produce segments of the test speech that are poorly matched to the claimed speaker model. A segment selection technique in score normalization is proposed that relies only on discriminative and reliable segments of the test utterance to verify the speaker. This approach is particularly useful in noisy conditions where using speech activity detection is not reliable at the feature level. Another source of score variability comes from the fact that not all phonemes are equally discriminative. To address this, a new score re-weighting technique is applied to likelihood values based on the discriminative level of each Gaussian component, i.e. each particular region of the feature space. It is found that a limited number of Gaussian mixtures, herein termed discriminative components are responsible for the overall performance, and that inclusion of the other non-discriminative components may only degrade the system performance.
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Viswanathan, Murlikrishna. "Towards robust discovery systems". Monash University, School of Computer Science and Software Engineering, 2003. http://arrow.monash.edu.au/hdl/1959.1/9397.
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Westendorp, James Computer Science & Engineering Faculty of Engineering UNSW. "Robust incremental relational learning". Awarded by:University of New South Wales. Computer Science & Engineering, 2009. http://handle.unsw.edu.au/1959.4/43513.
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Real-world learning tasks present a range of issues for learning systems. Learning tasks can be complex and the training data noisy. When operating as part of a larger system, there may be limitations on available memory and computational resources. Learners may also be required to provide results from a stream. This thesis investigates the problem of incremental, relational learning from imperfect data with constrained time and memory resources. The learning process involves incremental update of a theory when an example is presented that contradicts the theory. Contradictions occur if there is an incorrect theory or noisy data. The learner cannot discriminate between the two possibilities, so both are considered and the better possibility used. Additionally, all changes to the theory must have support from multiple examples. These two principles allow learning from imperfect data. The Minimum Description Length principle is used for selection between possible worlds and determining appropriate levels of additional justification. A new encoding scheme allows the use of MDL within the framework of Inductive Logic Programming. Examples must be stored to provide additional justification for revisions without violating resource requirements. A new algorithm determines when to discard examples, minimising total usage while ensuring sufficient storage for justifications. Searching for revisions is the most computationally expensive part of the process, yet not all searches are successful. Another new algorithm uses a notion of theory stability as a guide to occasionally disallow entire searches to reduce overall time. The approach has been implemented as a learner called NILE. Empirical tests include two challenging domains where this type of learner acts as one component of a larger task. The first of these involves recognition of behavior activation conditions in another agent as part of an opponent modeling task. The second, more challenging task is learning to identify objects in visual images by recognising relationships between image features. These experiments highlight NILE'S strengths and limitations as well as providing new n domains for future work in ILP.
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Pradhan, Sameer S. "Robust semantic role labeling". Diss., Connect to online resource, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3239377.
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Wülfert, Florian. "Temperature-robust multivariate calibration". [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2004. http://dare.uva.nl/document/76379.
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Jaganathan, Venkata Krishnan. "Robust motion estimation techniques". Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/6032.
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Thesis (M.S.)--University of Missouri-Columbia, 2007.The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 15, 2008) Includes bibliographical references.
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Jaehn, Florian. "Robust flight gate assignment". Frankfurt, M. Berlin Bern Bruxelles New York, NY Oxford Wien Lang, 2007. http://d-nb.info/987654136/04.
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Jaehn, Florian. "Robust flight gate assignment /". Frankfurt am Main [u.a.] : Lang, 2008. http://d-nb.info/987654136/04.
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Batur, Aziz Umit. "Illumination-robust face recognition". Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/15440.
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Witkowski, Jens [Verfasser], e Bernhard [Akademischer Betreuer] Nebel. "Robust peer prediction mechanisms". Freiburg : Universität, 2015. http://d-nb.info/1119805538/34.
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Yoon, Tae-Woong. "Robust adaptive predictive control". Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359527.
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