Дисертації з теми "Functional algorithms"
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King, David Jonathan. "Functional programming and graph algorithms." Thesis, University of Glasgow, 1996. http://theses.gla.ac.uk/1629/.
Повний текст джерелаKarmakar, Saurav. "Statistical Stability and Biological Validity of Clustering Algorithms for Analyzing Microarray Data." Digital Archive @ GSU, 2005. http://digitalarchive.gsu.edu/math_theses/3.
Повний текст джерелаDanilenko, Nikita [Verfasser]. "Designing Functional Implementations of Graph Algorithms / Nikita Danilenko." Kiel : Universitätsbibliothek Kiel, 2016. http://d-nb.info/1102933031/34.
Повний текст джерелаKlingner, John. "Distributed and Decentralized Algorithms for Functional Programmable Matter." Thesis, University of Colorado at Boulder, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10980638.
Повний текст джерелаProgrammable matter is made up of large quantities of particles that can sense, actuate, communicate, and compute. Motivated to imbue these materials with functionality, this thesis presents algorithmic and hardware developments to meet the unique challenges presented by large-scale robot collectives. The quantity of robots involved necessitates algorithms and processes which scale—in terms of required communication, computation, and memory—sub-linearly to the number of robots, if scaling at all can not be avoided. Included are methods for communication, movement, synchronization, and localization. To encourage application to a variety of hardware platforms, the theoretical underpinnings of these contributions are made as abstract as possible. These methods are tested experimentally with real hardware, using the Droplet swarm robotics platform I have developed. I also present abstractions which relate global performance properties of a functional object composed of programmable matter to local properties of the hardware platform from which the object is composed. This thesis is further supported by example implementations of functional objects on the Droplets: a TV remote control, a pong game, and a keyboard with mouse.
Hu, Jialu [Verfasser]. "Algorithms to Identify Functional Orthologs And Functional Modules from High-Throughput Data / Jialu Hu." Berlin : Freie Universität Berlin, 2015. http://d-nb.info/1064869807/34.
Повний текст джерелаIlberg, Peter. "Floyd : a functional programming language with distributed scope." Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/8187.
Повний текст джерелаDemir, Sumeyra Ummuhan. "Image Processing Algorithms for Diagnostic Analysis of Microcirculation." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/137.
Повний текст джерелаBelešová, Michaela. "Aplikace evolučního algoritmu při tvorbě regresních testů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236142.
Повний текст джерелаShafi, Muhammmad Imran, and Muhammad Akram. "Functional Approach towards Approximation Problem." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1245.
Повний текст джерелаMuhammad Imran Shafi: 29A Sodergatan 19547 Marsta, 0737171514, Muhammad Akram C/O Saad Bin Azhar Folkparksvagen 20/10 Ronneby, 0762899111
Toh, Justin Sieu-Sung. "Iterative diagonalisation algorithms in plane wave density functional theory with applications to surfaces." Thesis, University of Cambridge, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615143.
Повний текст джерелаBrown, Michael Scott. "A Species-Conserving Genetic Algorithm for Multimodal Optimization." NSUWorks, 2010. http://nsuworks.nova.edu/gscis_etd/104.
Повний текст джерелаVroon, Daron. "Automatically Proving the Termination of Functional Programs." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19734.
Повний текст джерела譚晓慧 and Xiaohui Tan. "Optimization and stability analysis on light-weight multi-functional smart structures using genetic algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41290707.
Повний текст джерелаScott, Daniel. "The discovery of new functional oxides using combinatorial techniques and advanced data mining algorithms." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/15214/.
Повний текст джерелаTan, Xiaohui. "Optimization and stability analysis on light-weight multi-functional smart structures using genetic algorithms." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41290707.
Повний текст джерелаDelgado, Reyes Lourdes Marielle. "Evaluating motion processing algorithms for use with fNIRS data from young children." Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/5929.
Повний текст джерелаAcharya, Vineeth Vadiraj. "Branch Guided Metrics for Functional and Gate-level Testing." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/51661.
Повний текст джерелаMaster of Science
Leroy, Arthur. "Multi-task learning models for functional data and application to the prediction of sports performances." Thesis, Université de Paris (2019-....), 2020. http://www.theses.fr/2020UNIP7089.
Повний текст джерелаThe present document is dedicated to the analysis of functional data and the definition of multi-task models for regression and clustering. The purpose of this work is twofold andfinds its origins in the problem of talent identification in elite sports. This context provides a leading thread illustrative example for the methods and algorithms introduced subsequently while also raising the problem of studying multiple time series, assumed to share information and generally observed on irregular grids. The central method and the associated algorithm developed in this thesis focus on the aspects of functional regression by using multi-task Gaussian processes (GPs) models. This non-parametric probabilistic framework proposes to define a prior distribution on functions, generating data associated with several individuals. Sharing information across those different individuals, through a mean process, offers enhanced modelling compared to a single-task GP, along with a thorough quantification of uncertainty. An extension of this model is then proposed from the definition of a multi-task GPs mixture. Such an approach allows us to extend the assumption of a unique underlying mean process to multiple ones, each being associated with a cluster of individuals. These two methods, respectively called Magma and MagmaClust, provide new insights on GP modelling as well as state-of-the-art performances both on prediction and clustering aspects. From the applicative point of view, the analyses focus on the study of performance curves of young swimmers, and preliminary exploration of the real datasets highlights the existence of different progression patterns during the career. Besides, the algorithm Magma provides, after training on a dataset, a probabilistic prediction of the future performances for each young swimmer, thus offering a valuable forecasting tool for talent identification. Finally, the extension proposed by MagmaClust allows the automatic construction of clusters of swimmers, according to their similarities in terms of progression patterns, leading once more to enhanced predictions. The methods proposed in this thesis have been entirely implemented and are freely available
Godichon-Baggioni, Antoine. "Algorithmes stochastiques pour la statistique robuste en grande dimension." Thesis, Dijon, 2016. http://www.theses.fr/2016DIJOS053/document.
Повний текст джерелаThis thesis focus on stochastic algorithms in high dimension as well as their application in robust statistics. In what follows, the expression high dimension may be used when the the size of the studied sample is large or when the variables we consider take values in high dimensional spaces (not necessarily finite). In order to analyze these kind of data, it can be interesting to consider algorithms which are fast, which do not need to store all the data, and which allow to update easily the estimates. In large sample of high dimensional data, outliers detection is often complicated. Nevertheless, these outliers, even if they are not many, can strongly disturb simple indicators like the mean and the covariance. We will focus on robust estimates, which are not too much sensitive to outliers.In a first part, we are interested in the recursive estimation of the geometric median, which is a robust indicator of location which can so be preferred to the mean when a part of the studied data is contaminated. For this purpose, we introduce a Robbins-Monro algorithm as well as its averaged version, before building non asymptotic confidence balls for these estimates, and exhibiting their $L^{p}$ and almost sure rates of convergence.In a second part, we focus on the estimation of the Median Covariation Matrix (MCM), which is a robust dispersion indicator linked to the geometric median. Furthermore, if the studied variable has a symmetric law, this indicator has the same eigenvectors as the covariance matrix. This last property represent a real interest to study the MCM, especially for Robust Principal Component Analysis. We so introduce a recursive algorithm which enables us to estimate simultaneously the geometric median, the MCM, and its $q$ main eigenvectors. We give, in a first time, the strong consistency of the estimators of the MCM, before exhibiting their rates of convergence in quadratic mean.In a third part, in the light of the work on the estimates of the median and of the Median Covariation Matrix, we exhibit the almost sure and $L^{p}$ rates of convergence of averaged stochastic gradient algorithms in Hilbert spaces, with less restrictive assumptions than in the literature. Then, two applications in robust statistics are given: estimation of the geometric quantiles and application in robust logistic regression.In the last part, we aim to fit a sphere on a noisy points cloud spread around a complete or truncated sphere. More precisely, we consider a random variable with a truncated spherical distribution, and we want to estimate its center as well as its radius. In this aim, we introduce a projected stochastic gradient algorithm and its averaged version. We establish the strong consistency of these estimators as well as their rates of convergence in quadratic mean. Finally, the asymptotic normality of the averaged algorithm is given
Robertson, Calum Stewart. "Parallel data mining on cycle stealing networks." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15970/1/Calum_Robertson_Thesis.pdf.
Повний текст джерелаRobertson, Calum Stewart. "Parallel Data Mining On Cycle Stealing Networks." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15970/.
Повний текст джерелаRosić, Bojana [Verfasser], and Hermann [Akademischer Betreuer] Matthies. "Variational Formulations and Functional Approximation Algorithms in Stochastic Plasticity of Materials / Bojana Rosic ; Betreuer: Hermann Matthies." Braunschweig : Technische Universität Braunschweig, 2012. http://d-nb.info/1175822434/34.
Повний текст джерелаKlipstein, Richard Henry. "Algorithms and mathematical methods for extraction of functional information from magnetic resonance images of the heart." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/47139.
Повний текст джерелаLiénard, Jean. "Models of the Basal Ganglia : Study of the Functional Anatomy and Pathophysiology using Multiobjective Evolutionary Algorithms." Paris 6, 2013. http://www.theses.fr/2013PA066125.
Повний текст джерелаOur work brings contributions to the field of computational models of the basal ganglia(BG) with the use of multi-objective evolutionary algorithms. We first characterized what underlies the hypothesized selection capability in the BG structure with two models : the CBG (Girard et al. 2008) and the GPR (Gurney et al. 2001). The direct/indirect pathway were found to be important; those of the thalamic loop, indifferent; the GPe → GPi/SNr projection, antagonist to selection. Two pathways explain the better selectivity in CBG: the GPe → MSN connection and the diffuse pattern of GPe → GPi/SNr. We also build plausible BG models which respect a collection of constraints issued from a review of anatomical and electrophysiological primate literature. Our first result is that anatomical and electrophysiological data are consistent if we suppose a GPe → GPi/SNr projection that is weakly inhibitory. Our second result is that the plausible models perform selection, with electrophysiological activities that are furthermore plausible. We finally studied the pattern of projection of the GPe → GPi/SNr projection, and found that a diffuse pattern is more efficient for selection. Finally, we studied with the plausible models the origin of the oscillations occurring in Parkinson’s disease. We first established delays matching the timing data from stimulation experiments. Modeling the dopamine depletion by a moderate plausible increase in single spike efficiency in STN, GPe and GPi/SNr is enough to trigger oscillatory regimens in the β-band. The oscillations frequency is highly dependent of the GPe ⇋ STN delays, which could not plausibly support - band oscillations in our models
Rizzo, Gaia. "Development of novel computational algorithms for quantitative voxel-wise functional brain imaging with positron emission tomography." Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3422179.
Повний текст джерелаLa Tomografia ad Emissione di Positroni (PET) permette di studiare, in vivo, l'interazione dei traccianti con specifici siti di legame (trasportatori, recettori, etc.). Inoltre permette un imaging funzionale quantitativo di importanti parametri fisiologici quali la densità di recettori, volume di distribuzione e/o occupazione recettoriale. In questa tesi si espone una panoramica dei principali metodi modellistici in PET e si propongono nuovi approcci Bayesiani sviluppati per la quantificazione a livello di voxel di immagini PET, applicati a vari dataset. I metodi proposti costituiscono una robusta alternativa per la generazione di mappe parametriche affidabili ed applicati a dati clinici renderanno più semplice il riconoscimento di piccole zone patologiche specifiche. Come ulteriore risultato, sono stati sviluppati nuovi modelli compartimentali per i dati di [11C]SCH442416 e [11C]MDL100907. Inoltre è stato implementato un nuovo metodo di clustering che permette di segmentare il volume cerebrale anche per dati PET con un alto livello di rumore. Questo nuovo approccio è stato applicato per la selezione della migliore regione di riferimento per dati di [11C]MDL100907.
Stojkovic, Ivan. "Functional Norm Regularization for Margin-Based Ranking on Temporal Data." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/522550.
Повний текст джерелаPh.D.
Quantifying the properties of interest is an important problem in many domains, e.g., assessing the condition of a patient, estimating the risk of an investment or relevance of the search result. However, the properties of interest are often latent and hard to assess directly, making it difficult to obtain classification or regression labels, which are needed to learn a predictive models from observable features. In such cases, it is typically much easier to obtain relative comparison of two instances, i.e. to assess which one is more intense (with respect to the property of interest). One framework able to learn from such kind of supervised information is ranking SVM, and it will make a basis of our approach. Applications in bio-medical datasets typically have specific additional challenges. First, and the major one, is the limited amount of data examples, due to an expensive measuring technology, and/or infrequency of conditions of interest. Such limited number of examples makes both identification of patterns/models and their validation less useful and reliable. Repeated samples from the same subject are collected on multiple occasions over time, which breaks IID sample assumption and introduces dependency structure that needs to be taken into account more appropriately. Also, feature vectors are highdimensional, and typically of much higher cardinality than the number of samples, making models less useful and their learning less efficient. Hypothesis of this dissertation is that use of the functional norm regularization can help alleviating mentioned challenges, by improving generalization abilities and/or learning efficiency of predictive models, in this case specifically of the approaches based on the ranking SVM framework. The temporal nature of data was addressed with loss that fosters temporal smoothness of functional mapping, thus accounting for assumption that temporally proximate samples are more correlated. Large number of feature variables was handled using the sparsity inducing L1 norm, such that most of the features have zero effect in learned functional mapping. Proposed sparse (temporal) ranking objective is convex but non-differentiable, therefore smooth dual form is derived, taking the form of quadratic function with box constraints, which allows efficient optimization. For the case where there are multiple similar tasks, joint learning approach based on matrix norm regularization, using trace norm L* and sparse row L21 norm was also proposed. Alternate minimization with proximal optimization algorithm was developed to solve the mentioned multi-task objective. Generalization potentials of the proposed high-dimensional and multi-task ranking formulations were assessed in series of evaluations on synthetically generated and real datasets. The high-dimensional approach was applied to disease severity score learning from gene expression data in human influenza cases, and compared against several alternative approaches. Application resulted in scoring function with improved predictive performance, as measured by fraction of correctly ordered testing pairs, and a set of selected features of high robustness, according to three similarity measures. The multi-task approach was applied to three human viral infection problems, and for learning the exam scores in Math and English. Proposed formulation with mixed matrix norm was overall more accurate than formulations with single norm regularization.
Temple University--Theses
More, Joshua N. "Algorithms and computer code for ab initio path integral molecular dynamics simulations." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:b8ca7471-21e3-4240-95b1-8775e5d6c08f.
Повний текст джерелаWu, Jiann-Yuarn. "A study of a moving contact algorithm." Thesis, Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/80074.
Повний текст джерелаMaster of Science
Castiel, Eyal. "Study of QB-CSMA algorithms." Thesis, Toulouse, ISAE, 2019. http://www.theses.fr/2019ESAE0038.
Повний текст джерелаPerformance of wireless networks, in which users share the air as support for their communications is strongly limited by electromagnetic interference. That is, two users close to each other trying to send a message on the same frequency will experience interference between their messages, eventually leading to the loss of some information. It is then crucial to develop medium access protocols aiming to limit the occurrence of such a phenomena by choosing in an effective (and distributed) manner which station is allowed to transmit. From a scientific point of view, it is a difficult issue which has had some attention from the community in the field of computer science and applied probability in the past 30 years. Recently, a new class of medium access protocols - called adaptive CSMA - emerged and seem quite promising: for example, it has been shown that they exhibit a desirable property: throughput optimality (maximum stability). The goal of this project is to increase the knowledge we have the adaptive CSMA (or CSMA QB, for Queue Based) which is to this day quite limited (notably in the expected waiting time of a request arriving in the system, called delay). Our goal will be to prove theoric results to enhance our understanding of the throughput/delay trade-off
Cannon, Jordan. "Statistical analysis and algorithms for online change detection in real-time psychophysiological data." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/342.
Повний текст джерелаMabaso, Bongani Andy. "Robots are not ethical like people : an exemplarist framework for functional ethics in everyday robots in ordinary contexts." Thesis, University of Pretoria, 2020. http://hdl.handle.net/2263/76011.
Повний текст джерелаThesis (PhD)--University of Pretoria, 2020.
Philosophy
PhD
Unrestricted
Pendurkar, Rajesh. "Design for testability techniques and optimization algorithms for performance and functional testing of mult-chip module interconnections." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/16635.
Повний текст джерелаArkoudas, Kostas. "On the termination of recursive algorithms in pure first-order functional languages with monomorphic inductive data types." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/39074.
Повний текст джерелаShinde, Swapnil Sadashiv. "Radio Access Network Function Placement Algorithms in an Edge Computing Enabled C-RAN with Heterogeneous Slices Demands." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20063/.
Повний текст джерелаFranco, Ricardo Augusto Pereira. "Vericação funcional de sistemas digitais utilizando algoritmos genéticos na geração de dados aplicada a metodologia veriSC." Universidade Federal de Goiás, 2014. http://repositorio.bc.ufg.br/tede/handle/tede/5028.
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The process of creating an Intellectual Property Core (IP-core) has become more complex with the advent of electronic circuit technology, encouraging the development of new techniques and methodologies to assist this process. A fundamental and critical stage of a hardware design is the hardware verification phase. At this phase it is verified that the IP-core was implemented according to their specification, ensuring that it is feasible to prototyping and their large-scale production (System on Chip). The verification phase corresponds to the biggest bottleneck in a hardware design (BERGERON,2006). The VeriSC methodology is an implemented methodology to perform the hardware verifi- cation through simulation, that is, by means of functional verification. This work aims to complement the VeriSC methodology through the development of an algorithm based on the concept of Genetic Algorithms (GAs). The proposed algorithm will modify the data generation of this methodology, whose objective is to reduce the verification time and to improve the generated data by changing the data from pseudorandom mode to random-guided mode, increasing the reliability of the verification performed by the VeriSC methodology. The algorithm has a generic part (templates) that helps the implementation of new environment for the functional verification of new DUVs and it can be incorpo- rated into other functional verification methodologies. Finally, are presented three case studies, the stimuli created using GA are compared with the old implementation of VeriSC methodology.
O processo de criação de um Intellectual Property Core (IP-core) vem se tornando cada vez mais complexo com o advento da tecnologia dos circuitos eletrônicos, incentivando o desenvolvimento de novas técnicas e metodologias que auxiliem esse processo. Uma das fases fundamentais e críticas de um projeto de hardware é a fase de verificação de hardware. É nesta fase que se verifica se o IP-core foi implementado de acordo com sua especificação, garantindo que seja viável sua prototipação e, posteriormente, sua produção em larga escala (System on Chip). A fase de verificação corresponde ao maior gargalo dentro de um projeto de hardware (BERGERON,2006). A metodologia VeriSC é uma metodologia desenvolvida para realizar a verificação de hardware através da simulação, isto é, por meio da verificação funcional. Este trabalho visa complementar a metodologia VeriSC por meio do desenvolvimento de um algoritmo baseado no conceito de Algoritmos Genéticos (AGs). O algoritmo proposto ira modificar a geração de dados dessa metodologia objetivando reduzir o tempo de verificação e aprimorar os dados gerados, alterando a geração de dados da forma pseudoaleatória para aleatória- guiado, aumentando, assim, a confiabilidade da verificação realizada pela metodologia VeriSC. O algoritmo possui partes genéricas (templates ) que facilita sua implementação na verificação de novos projetos de hardware e pode ser incorporado em outras metodologias de verificação funcional. Por fim, serão apresentados os resultados experimentais da aplicação da nova geração de dados em três estudos de casos, comparando-os com a implementação antiga da metodologia VeriSC.
Castellanos, Lucia. "Statistical Models and Algorithms for Studying Hand and Finger Kinematics and their Neural Mechanisms." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/273.
Повний текст джерелаVieira, Milreu Paulo. "Enumerating functional substructures of genome-scale metabolic networks : stories, precursors and organisations." Phd thesis, Université Claude Bernard - Lyon I, 2012. http://tel.archives-ouvertes.fr/tel-00850704.
Повний текст джерелаGuan, Wei. "New support vector machine formulations and algorithms with application to biomedical data analysis." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41126.
Повний текст джерелаKoskinen, M. (Miika). "Automatic assessment of functional suppression of the central nervous system due to propofol anesthetic infusion:from EEG phenomena to a quantitative index." Doctoral thesis, University of Oulu, 2006. http://urn.fi/urn:isbn:9514281756.
Повний текст джерелаHnízdilová, Bohdana. "Registrace ultrazvukových sekvencí s využitím evolučních algoritmů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442502.
Повний текст джерелаZhong, Cuncong. "Computational Methods for Comparative Non-coding RNA Analysis: From Structural Motif Identification to Genome-wide Functional Classification." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5894.
Повний текст джерелаPh.D.
Doctorate
Computer Science
Engineering and Computer Science
Computer Science
Кунцев, С. В. "Функціональні особливості GUI–інтерфейсу бібліотеки алгоритмів Xelopes". Thesis, Харківський національний економічний університет, 2009. http://essuir.sumdu.edu.ua/handle/123456789/62723.
Повний текст джерелаThe library of algorithms of Xelopes comes into a notice the features - support of standards of Data Mining, by independence from a platform, by independence from a weekend given, by availability. For providing of comfort together with a library as separate to addition a graphic man-machine (GUI) interface is supplied. The functional features of interface are in-process considered: loading of data; viewing of data is as a table; viewing of attributes given; viewing of statistical information is about data; construction of model of Data Mining; visualization of model; maintenance of model; application of model.
Ragnehed, Mattias. "Functional Magnetic Resonance Imaging for Clinical Diagnosis : Exploring and Improving the Examination Chain." Doctoral thesis, Linköping : Department of Medical and Health Sciences, Linköping University, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-18095.
Повний текст джерелаMounirou, Arouna Lukman Moctar. "Construction automatique d'images de pseudo-âges géologiques à partir d'images sismiques par minimisation d'énergie." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0232/document.
Повний текст джерелаThe objective of the thesis is to propose a segmentation of an underlying seismic image in perfect coherence with the results of a preliminary analysis by an expert (horizons, faults). laws of geology. The originality of the approach will be to develop techniques for segmenting seismic images, among others based on active contour type approaches, constrained by data interpreted in addition to intrinsic properties calculated by automatic processes from the data processed without requiring any supervision in contrast to existing work. A second axis will be to automatically schedule the horizons (surfaces) interpreted and to analyze each interval (the place between two horizons) finely, taking into account its content (amplitude, orientation, etc.). All this resulted in the reconstruction of the geological pseudo-time
Gomes, Victor pereira. "Funções recursivas primitivas: caracterização e alguns resultados para esta classe de funções." Universidade Federal da Paraíba, 2016. http://tede.biblioteca.ufpb.br:8080/handle/tede/8514.
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The class of primitive recursive functions is not a formal version to the class of algorithmic functions, we study this special class of numerical functions due to the fact of that many of the functions known as algorithmic are primitive recursive. The approach on the class of primitive recursive functions aims to explore this special class of functions and from that, present solutions for the following problems: (1) given the class of primitive recursive derivations, is there an algorithm, that is, a mechanical procedure for recognizing primitive recursive derivations? (2) Is there a universal function for the class of primitive recursive functions? If so, is this function primitive recursive? (3) Are all the algorithmic functions primitive recursive? To provide solutions to these issues, we base on the hypothetical-deductive method and argue based on the works of Davis (1982), Mendelson (2009), Dias e Weber (2010), Rogers (1987), Soare (1987), Cooper (2004), among others. We present the theory of Turing machines which is a formal version to the intuitive notion of algorithm, and after that the famous Church-Turing tesis which identifies the class of algorithmic functions with the class of Turing-computable functions. We display the class of primitive recursive functions and show that it is a subclass of Turing-computable functions. Having explored the class of primitive recursive functions we proved as results that there is a recognizer algorithm to the class of primitive recursive derivations; that there is a universal function to the class of primitive recursive functions which does not belong to this class; and that not every algorithmic function is primitive recursive.
A classe das funções recursivas primitivas não constitui uma versão formal para a classe das funções algorítmicas, estudamos esta classe especial de funções numéricas devido ao fato de que muitas das funções conhecidas como algorítmicas são recursivas primitivas. A abordagem acerca da classe das funções recursivas primitivas tem como objetivo explorar esta classe especial de funções e, a partir disto, apresentar soluções para os seguintes problemas: (1) dada a classe das derivações recursivas primitivas, há um algoritmo, ou seja, um procedimento mecânico, para reconhecer derivações recursivas primitivas? (2) Existe uma função universal para a classe das funções recursivas primitivas? Se sim, essa função é recursiva primitiva? (3) Toda função algorítmica é recursiva primitiva? Para apresentar soluções para estas questões, nos pautamos no método hipotético-dedutivo e argumentamos com base nos manuais de Davis (1982), Mendelson (2009), Dias e Weber (2010), Rogers (1987), Soare (1987), Cooper (2004), entre outros. Apresentamos a teoria das máquinas de Turing, que constitui uma versão formal para a noção intuitiva de algoritmo, e, em seguida, a famosa tese de Church-Turing, a qual identifica a classe das funções algorítmicas com a classe das funções Turing-computáveis. Exibimos a classe das funções recursivas primitivas, e mostramos que a mesma constitui uma subclasse das funções Turing-computáveis. Tendo explorado a classe das funções recursivas primitivas, como resultados, provamos que existe um algoritmo reconhecedor para a classe das derivações recursivas primitivas; que existe uma função universal para a classe das funções recursivas primitivas a qual não pertence a esta classe; e que nem toda função algorítmica é recursiva primitiva.
Stacha, Radek. "Optimalizace kogeneračního systému." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-231502.
Повний текст джерелаHeil, Katharina Friedlinde. "Systems biological approach to Parkinson's disease." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31043.
Повний текст джерелаGötz, Andreas W. [Verfasser], and Andreas [Akademischer Betreuer] Görling. "The Limited Expansion of Diatomic Overlap Density Functional Theory (LEDO-DFT): Development and Implementation of Algorithms, Optimization of Auxiliary Orbitals and Benchmark Calculations / Andreas Walter Götz. Betreuer: Andreas Görling." Erlangen : Universitätsbibliothek der Universität Erlangen-Nürnberg, 2005. http://d-nb.info/1035574977/34.
Повний текст джерелаWhitinger, Robert. "An Algorithm for the Machine Calculation of Minimal Paths." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3119.
Повний текст джерелаCorman, Etienne. "Functional representation of deformable surfaces for geometry processing." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLX075/document.
Повний текст джерелаCreating and understanding deformations of surfaces is a recurring theme in geometry processing. As smooth surfaces can be represented in many ways from point clouds to triangle meshes, one of the challenges is being able to compare or deform consistently discrete shapes independently of their representation. A possible answer is choosing a flexible representation of deformable surfaces that can easily be transported from one structure to another.Toward this goal, the functional map framework proposes to represent maps between surfaces and, to further extents, deformation of surfaces as operators acting on functions. This approach has been recently introduced in geometry processing but has been extensively used in other fields such as differential geometry, operator theory and dynamical systems, to name just a few. The major advantage of such point of view is to deflect challenging problems, such as shape matching and deformation transfer, toward functional analysis whose discretization has been well studied in various cases. This thesis investigates further analysis and novel applications in this framework. Two aspects of the functional representation framework are discussed.First, given two surfaces, we analyze the underlying deformation. One way to do so is by finding correspondences that minimize the global distortion. To complete the analysis we identify the least and most reliable parts of the mapping by a learning procedure. Once spotted, the flaws in the map can be repaired in a smooth way using a consistent representation of tangent vector fields.The second development concerns the reverse problem: given a deformation represented as an operator how to deform a surface accordingly? In a first approach, we analyse a coordinate-free encoding of the intrinsic and extrinsic structure of a surface as functional operator. In this framework a deformed shape can be recovered up to rigid motion by solving a set of convex optimization problems. Second, we consider a linearized version of the previous method enabling us to understand deformation fields as acting on the underlying metric. This allows us to solve challenging problems such as deformation transfer are solved using simple linear systems of equations