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Relevant bibliographies by topics / Nonlinear adaptive models

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Academic literature on the topic 'Nonlinear adaptive models'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Nonlinear adaptive models"

1

Shapiro, Arnold F., and R. Paul Gorman. "Implementing adaptive nonlinear models." Insurance: Mathematics and Economics 26, no. 2-3 (May 2000): 289–307. http://dx.doi.org/10.1016/s0167-6687(00)00036-6.

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Priscoli, F. Delli, L. Marconi, and A. Isidori. "Adaptive observers as nonlinear internal models." Systems & Control Letters 55, no. 8 (August 2006): 640–49. http://dx.doi.org/10.1016/j.sysconle.2005.09.016.

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Ye, Xudong. "Nonlinear adaptive control using multiple identification models." Systems & Control Letters 57, no. 7 (July 2008): 578–84. http://dx.doi.org/10.1016/j.sysconle.2007.12.007.

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Coad, D. S., and M. B. Woodroofe. "Corrected confidence intervals for adaptive nonlinear regression models." Journal of Statistical Planning and Inference 130, no. 1-2 (March 2005): 63–83. http://dx.doi.org/10.1016/j.jspi.2004.02.020.

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Murray-Smith, Roderick, and Daniel Sbarbaro. "NONLINEAR ADAPTIVE CONTROL USING NONPARAMETRIC GAUSSIAN PROCESS PRIOR MODELS." IFAC Proceedings Volumes 35, no. 1 (2002): 325–30. http://dx.doi.org/10.3182/20020721-6-es-1901.01040.

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Fink, Alexander, Martin Fischer, and Oliver Nelles. "Supervision of nonlinear adaptive controllers based on fuzzy models." IFAC Proceedings Volumes 32, no. 2 (July 1999): 8602–7. http://dx.doi.org/10.1016/s1474-6670(17)57467-4.

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Chen, Lingji, and Kumpati S. Narendra. "Nonlinear adaptive control using neural networks and multiple models." Automatica 37, no. 8 (August 2001): 1245–55. http://dx.doi.org/10.1016/s0005-1098(01)00072-3.

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McLain, Richard B., and Michael A. Henson. "Nonlinear Model Reference Adaptive Control with Embedded Linear Models." Industrial & Engineering Chemistry Research 39, no. 8 (August 2000): 3007–17. http://dx.doi.org/10.1021/ie990088t.

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Fink, Alexander, Martin Fischer, Oliver Nelles, and Rolf Isermann. "Supervision of nonlinear adaptive controllers based on fuzzy models." Control Engineering Practice 8, no. 10 (October 2000): 1093–105. http://dx.doi.org/10.1016/s0967-0661(00)00059-9.

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Ma, Zixiao, Zhaoyu Wang, Yifei Guo, Yuxuan Yuan, and Hao Chen. "Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids." IEEE Transactions on Smart Grid 12, no. 1 (January 2021): 227–38. http://dx.doi.org/10.1109/tsg.2020.3023307.

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Dissertations / Theses on the topic "Nonlinear adaptive models"

1

Harkness, John. "Walsh functions for the identification and control of nonlinear plants." Thesis, University of Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.281832.

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Adam, Wettring. "Adaptive Filtering and Nonlinear Models for Post-processing of Weather Forecasts." Thesis, Linköpings universitet, Reglerteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119642.

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Kalman filters have been used by SMHI to improve the quality of their forecasts. Until now they have used a linear underlying model to do this. In this thesis it is investigated whether the performance can be improved by the use of nonlinear models such as polynomials and neural networks. The results suggest that an improvement is hard to achieve by this approach and that it is likely not worth the effort to implement a nonlinear model.

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McCallum, Emma Clare. "Adaptive phase II clinical trial design using nonlinear dose-response models." Thesis, University of Cambridge, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709013.

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CERBONI, BAIARDI LORENZO. "Adaptive models of learning in complex physical and social systems." Doctoral thesis, Urbino, 2016. http://hdl.handle.net/11576/2630552.

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Mazumdar, Sanjay Kumar. "Adaptive control of nonlinear systems using neural networks /." Title page, contents and abstract only, 1995. http://web4.library.adelaide.edu.au/theses/09PH/09phm476.pdf.

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Ton, That Long. "Nonlinear control studies for circadian models in system biology." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/nonlinear-control-studies-for-circadian-models-in-system-biology(f616f360-99e4-4314-ba51-be7a49e9ff0e).html.

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Circadian rhythms exist in almost all of living species, and they occupy an important role in daily biological activities of these species. This thesis deals with reduction of measurements in circadian models, and recovery of circadian phases. Two mathematical models of circadian rhythms are considered, with a 3rd order model for Neurospora, and a 7th order model for Mammals. The reduction of measurements of circadian models is shown by the proposals of observer designs to the two mathematical models of circadian rhythms. Both mathematical models contain strong nonlinearities, which make the observer design challenging. Two observer designs, reduced-order and one-sided Lipschitz, are applied to the circadian models to tackle the nonlinearities. Reduced-order observer design is based on a state transformation to make certain nonlinearities have no impact on the observer errors, and the design of one-sided Lipschitz observer is based on systems with one-sided Lipschitz nonlinearities. Both observer designs are based on the existing methods in literature. The existing method of reduced-order observer has been applied to a class of multi-output nonlinear systems. A new reduced-order observer design which extends the existing one in literature is presented in this thesis. In this new reduced-order observer method, the observer error dynamics can be designed by choosing the observer gain, unlike the existing one, of which the observer error dynamics depend on the invariant zeros under certain input-output map. The recovery of circadian phases is carried out to provide a solution to phase shifts occurred in circadian disorders. The restoration of circadian phases is performed by the synchronizations of trajectories of a controlled model with trajectories of a reference model. The reference model and the controlled model have phase differences, and both these models are based on a given 3rd order model of Neurospora circadian rhythms. The phase differences are reflected by different initial conditions, and by parameter uncertainty. The synchronizations of the two models are performed by using back-stepping method for the case of different initial conditions, and by using adaptive back-stepping method for the remaining case. Several simulation studies of the proposed observer designs and the proposed schemes of synchronizations are carried out with the results shown in this thesis.

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Eckardt, Stefan Verfasser], and Carsten [Akademischer Betreuer] [Könke. "Adaptive heterogeneous multiscale models for the nonlinear simulation of concrete / Stefan Eckardt ; Betreuer: Carsten Könke." Weimar : Institut für Strukturmechanik, 2010. http://d-nb.info/1115806408/34.

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Strömberg, Eric. "Applied Adaptive Optimal Design and Novel Optimization Algorithms for Practical Use." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-308452.

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The costs of developing new pharmaceuticals have increased dramatically during the past decades. Contributing to these increased expenses are the increasingly extensive and more complex clinical trials required to generate sufficient evidence regarding the safety and efficacy of the drugs. It is therefore of great importance to improve the effectiveness of the clinical phases by increasing the information gained throughout the process so the correct decision may be made as early as possible. Optimal Design (OD) methodology using the Fisher Information Matrix (FIM) based on Nonlinear Mixed Effect Models (NLMEM) has been proven to serve as a useful tool for making more informed decisions throughout the clinical investigation. The calculation of the FIM for NLMEM does however lack an analytic solution and is commonly approximated by linearization of the NLMEM. Furthermore, two structural assumptions of the FIM is available; a full FIM and a block-diagonal FIM which assumes that the fixed effects are independent of the random effects in the NLMEM. Once the FIM has been derived, it can be transformed into a scalar optimality criterion for comparing designs. The optimality criterion may be considered local, if the criterion is based on singe point values of the parameters or global (robust), where the criterion is formed for a prior distribution of the parameters. Regardless of design criterion, FIM approximation or structural assumption, the design will be based on the prior information regarding the model and parameters, and is thus sensitive to misspecification in the design stage. Model based adaptive optimal design (MBAOD) has however been shown to be less sensitive to misspecification in the design stage. The aim of this thesis is to further the understanding and practicality when performing standard and MBAOD. This is to be achieved by: (i) investigating how two common FIM approximations and the structural assumptions may affect the optimized design, (ii) reducing runtimes complex design optimization by implementing a low level parallelization of the FIM calculation, (iii) further develop and demonstrate a framework for performing MBAOD, (vi) and investigate the potential advantages of using a global optimality criterion in the already robust MBAOD.

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Minggao, Wei. "Human Head Stiffness Rendering." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32743.

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The technology of haptics rendering has greatly enriched development in Multimedia applications, such as teleoperation, gaming, medical and etc., because it makes the virtual object touchable by the human operator(s) in real world. Human head stiffness rendering is significant in haptic interactive applications as it defines the degree of reality in physical interaction of a human avatar created in virtual environment. In a similar research, the haptic rendering approach has two main types: 1) Haptic Information Integration and 2) Deformation Simulation. However, the complexity in anatomic and geometric structure of a human head makes the rendering procedure challenging because of the issues of accuracy and efficiency. In this work, we propose a hybrid method to render the appropriate stiffness property onto a 3D head polygon mesh of an individual user by firstly studying human head's sophisticated deformation behaviour and then rendering such behaviour as the resultant stiffness property on the polygon mesh. The stiffness property is estimated from a semantically registered and shape-adapted skull template mesh as a reference and modeled from soft tissue's deformation behaviour in a nonlinear Finite Element Method (FEM) framework. To render the stiffness property, our method consists of different procedures, including 3D facial landmark detection, models semantic registration using Iterative Closest Point (ICP) technique, adaptive shape modification processed with a modified Weighted Free-Form Deformation (FFD) and FEM Simulation. After the stiffness property is rendered on a head polygon mesh, we perform a user study by inviting participants to experience the haptic feedback rendered from our results. According to the participants' feedback, the head polygon mesh's stiffness property is properly rendered as it satisfies their expectation.

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MANICKAM, NITHYA. "NONLINEAR AND ADAPTIVE CONTROL OF MODEL HELICOPTER." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1144639875.

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Books on the topic "Nonlinear adaptive models"

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Mandic, Danilo P. Complex valued nonlinear adaptive filters: Noncircularity, widely linear, and neural models. Hoboken, N.J: Wiley, 2009.

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Nassirharand, Amir. Computer-aided nonlinear control system design: Using describing function models. London: Springer, 2012.

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Läuter, Matthias. Grossäumige Zirkulationsstrukturen in einem nichtlinearen adaptiven atmosphärenmodell =: Large-scale circulation structures in a nonlinear adaptive model of the atmosphere. Bremerhaven: Alfred-Wegener-Institut für Polar- und Meeresforschung, 2005.

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service), SpringerLink (Online, ed. Delay compensation for nonlinear, adaptive, and PDE systems. Boston, Mass: Birkhäuser, 2009.

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Lewis, Peter A. W. Nonlinear modeling of time series using Multivariate Adaptive Regression Splines (MARS). Monterey, Calif: Naval Postgraduate School, 1990.

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Zourntos, Takis. Nonlinear adaptive control based on the related model. Ottawa: National Library of Canada, 1996.

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Luo, W. Adaptive model selection and estimation for nonlinear systems using a sliding data window. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1994.

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United States. National Aeronautics and Space Administration., ed. Adaptive performance seeking control using fuzzy model reference learning control and positive gradient control. Washington, DC: National Aeronautics and Space Administration, 1997.

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Mandic, Danilo, and Vanessa (Su Lee) Goh. Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models. Wiley & Sons, Limited, John, 2009.

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Mandic, Danilo P., and Vanessa Su Lee Goh. Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models. Wiley & Sons, Incorporated, John, 2009.

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Book chapters on the topic "Nonlinear adaptive models"

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Zhang, Heping. "Mixed-Effects Multivariate Adaptive Splines Models." In Nonlinear Estimation and Classification, 297–306. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21579-2_18.

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Marusak, Piotr M. "Efficient Model Predictive Control Algorithm with Fuzzy Approximations of Nonlinear Models." In Adaptive and Natural Computing Algorithms, 448–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04921-7_46.

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Ławryńczuk, Maciej. "Nonlinear Predictive Control Based on Multivariable Neural Wiener Models." In Adaptive and Natural Computing Algorithms, 31–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20282-7_4.

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Saxén, Henrik, and Frank Pettersson. "A Methodology for Developing Nonlinear Models by Feedforward Neural Networks." In Adaptive and Natural Computing Algorithms, 72–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04921-7_8.

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Hussain, M. A., J. C. Allwright, and L. S. Kershenbaum. "Adaptive Nonlinear Control — Linearised models with Neural Networks." In Neural Networks: Artificial Intelligence and Industrial Applications, 377–80. London: Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-3087-1_67.

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Ławryńczuk, Maciej. "Computationally Efficient Nonlinear Predictive Control Based on RBF Neural Multi-models." In Adaptive and Natural Computing Algorithms, 89–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04921-7_10.

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Lai, Tze Leung, and Vibhav Bukkapatanam. "Adaptive Filtering, Nonlinear State-Space Models, and Applications in Finance and Econometrics." In State-Space Models, 3–22. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7789-1_1.

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Ławryńczuk, Maciej. "Nonlinear Predictive Control Based on Least Squares Support Vector Machines Hammerstein Models." In Adaptive and Natural Computing Algorithms, 246–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37213-1_26.

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Lendek, Zsófia, Thierry Marie Guerra, Robert Babuška, and Bart De Schutter. "Adaptive Observers for TS Systems." In Stability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy Models, 149–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16776-8_7.

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Marusak, Piotr M. "Disturbance Measurement Utilization in the Efficient MPC Algorithm with Fuzzy Approximations of Nonlinear Models." In Adaptive and Natural Computing Algorithms, 307–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37213-1_32.

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Conference papers on the topic "Nonlinear adaptive models"

1

Nihtila, Markku. "Discrete adaptive control of nonlinear models." In 1985 24th IEEE Conference on Decision and Control. IEEE, 1985. http://dx.doi.org/10.1109/cdc.1985.268539.

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Ye Xudong. "Nonlinear adaptive control using multiple identification models." In 2008 Chinese Control Conference (CCC). IEEE, 2008. http://dx.doi.org/10.1109/chicc.2008.4605554.

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Dreesen, Philippe, Koen Tiels, Mariya Ishteva, and Johan Schoukens. "Nonlinear system identification: Finding structure in nonlinear black-box models." In 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2017. http://dx.doi.org/10.1109/camsap.2017.8313214.

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Mahmoodi, S. Nima, Ehsan Omidi, and Christian Rankl. "Nonlinear Dynamic Models of Piezoelectric Nano-Stages." In ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/smasis2016-9228.

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High resolution imaging in scanning probe microscopes is conducted by rastering a sharp probe over a sample surface. The rastering is done using piezoelectric elements, converting applied voltage into mechanical motion. For example, imaging of a rectangular field of view is done by applying triangular waveforms with different frequencies to X and Y piezoelectric stage, respectively. A disadvantage of piezoelectric stages is their non-linear response to applied voltage. In addition to that, they show creep, i.e. moving even though the applied voltage is constant. This results in distortions of the acquired image. Furthermore, it can result in not precisely imaging the requested area. A common solution is to add position sensors to the piezoelectric stages and measure actual movements. By using a feedback it would be almost guaranteed that the piezoelectric stage moves as requested. The disadvantage of this approach is that it reduces the bandwidth and increases the noise. The aim of this paper is to study advanced piezoelectric stage models to better control the actual stage movement in an open-loop scan.

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Zwierzewicz, Zenon. "Adaptive tracking control of uncertain SISO nonlinear systems." In 2012 17th International Conference on Methods & Models in Automation & Robotics (MMAR). IEEE, 2012. http://dx.doi.org/10.1109/mmar.2012.6347863.

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Wen, Liyan, Gang Tao, and Hao Yang. "Adaptive turbulence compensation for multivariable nonlinear aircraft models." In 2015 American Control Conference (ACC). IEEE, 2015. http://dx.doi.org/10.1109/acc.2015.7172209.

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Kabzinski, Jacek, and Przemyslaw Mosiolek. "Adaptive control of nonlinear resonant systems with damping." In 2015 20th International Conference on Methods and Models in Automation and Robotics (MMAR ). IEEE, 2015. http://dx.doi.org/10.1109/mmar.2015.7283953.

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Selisteanu, Dan, Emil Petre, Dorin Sendrescu, and Monica Roman. "Nonlinear indirect adaptive control of a Fed-batch fermentation Bioprocess." In 2012 17th International Conference on Methods & Models in Automation & Robotics (MMAR). IEEE, 2012. http://dx.doi.org/10.1109/mmar.2012.6347861.

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Chen, L., and K. S. Narendra. "Nonlinear adaptive control using neural networks and multiple models." In Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.877012.

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Narendra, K. S., and K. George. "Adaptive control of simple nonlinear systems using multiple models." In Proceedings of 2002 American Control Conference. IEEE, 2002. http://dx.doi.org/10.1109/acc.2002.1023824.

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Reports on the topic "Nonlinear adaptive models"

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Eguchi, Hiroaki, Takanori Fukao, and Koichi Osuka. Design Method of Reference Model for Active Steering Based on Nonlinear Adaptive D* Control. Warrendale, PA: SAE International, September 2005. http://dx.doi.org/10.4271/2005-08-0423.

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Nobile, F., Q. Ayoul-Guilmard, S. Ganesh, M. Nuñez, A. Kodakkal, C. Soriano, and R. Rossi. D6.5 Report on stochastic optimisation for wind engineering. Scipedia, 2022. http://dx.doi.org/10.23967/exaqute.2022.3.04.

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This report presents the latest methods of optimisation under uncertainties investigated in the ExaQUte project, and their applications to problems related to civil and wind engineering. The measure of risk throughout the report is the conditional value at risk. First, the reference method is presented: the derivation of sensitivities of the risk measure; their accurate computation; and lastly, a practical optimisation algorithm with adaptive statistical estimation. Second, this method is directly applied to a nonlinear relaxation oscillator (FitzHugh–Nagumo model) with numerical experiments to demonstrate its performance. Third, the optimisation method is adapted to the shape optimisation of an airfoil and illustrated by a large-scale experiment on a computing cluster. Finally, the benchmark of the shape optimisation of a tall building under a turbulent flow is presented, followed by an adaptation of the optimisation method. All numerical experiments showcase the open-source software stack of the ExaQUte project for large-scale computing in a distributed environment.

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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2015. http://dx.doi.org/10.55274/r0010891.

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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform lighting conditions. In the second part of the framework, the context-based segmentation is developed to eliminate regions from imagery that are not considered to be a threat to the pipeline. Context based segmentation makes use of a cascade of pre-trained classifiers to search for regions that are not threats. The context based segmentation algorithm accelerates threat identification and improves object detection rates. The last phase of the framework is an efficient object detection model. Efficient object detection �follows a three-stage approach which includes extraction of the local phase in the image and the use of local phase characteristics to locate machinery threats. The local phase is an image feature extraction technique which partially removes the lighting variance and preserves the edge information of the object. Multiple orientations of the same object are matched and the correct orientation is selected using feature matching by histogram of local phase in a multi-scale framework. The classifier outputs locations of threats to pipeline.�The advanced automatic image analysis system is intended to be capable of detecting construction equipment along the ROW of pipelines with a very high degree of accuracy in comparison with manual threat identification by a human analyst. �

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Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.

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The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. The most popular platform for mass information and social interaction is, first of all, network journalism, which is characterized by mobility and unlimited time and space. Authors have complete freedom to express their views in direct language, including their own word formation. Phonetic, lexical, phraseological and stylistic means of speech create expression of the text. A figurative word, a good aphorism or proverb, a paraphrased expression, etc. enhance the effectiveness of a multimedia text. This is especially important for headlines that simultaneously inform and influence the views of millions of readers. Given the wide range of issues raised by the Internet as a medium, research in this area is interdisciplinary. The science of information, combining language and social communication, is at the forefront of global interactions. The Internet is an effective source of knowledge and a forum for free thought. Nonlinear texts (hypertexts) – «branching texts or texts that perform actions on request», multimedia texts change the principles of information collection, storage and dissemination, involving billions of readers in the discussion of global issues. Mastering the word is not an easy task if the author of the publication is not well-read, is not deep in the topic, does not know the psychology of the audience for which he writes. Therefore, the study of media broadcasting is an important component of the professional training of future journalists. The functions of the language of the media require the authors to make the right statements and convincing arguments in the text. Journalism education is not only knowledge of imperative and dispositive norms, but also apodictic ones. In practice, this means that there are rules in media creativity that are based on logical necessity. Apodicticity is the first sign of impressive language on the platform of print or electronic media. Social expression is a combination of creative abilities and linguistic competencies that a journalist realizes in his activity. Creative self-expression is realized in a set of many important factors in the media: the choice of topic, convincing arguments, logical presentation of ideas and deep philological education. Linguistic art, in contrast to painting, music, sculpture, accumulates all visual, auditory, tactile and empathic sensations in a universal sign – the word. The choice of the word for the reproduction of sensory and semantic meanings, its competent use in the appropriate context distinguishes the journalist-intellectual from other participants in forums, round tables, analytical or entertainment programs. Expressive speech in the media is a product of the intellect (ability to think) of all those who write on socio-political or economic topics. In the same plane with him – intelligence (awareness, prudence), the first sign of which (according to Ivan Ogienko) is a good knowledge of the language. Intellectual language is an important means of organizing a journalistic text. It, on the one hand, logically conveys the author’s thoughts, and on the other – encourages the reader to reflect and comprehend what is read. The richness of language is accumulated through continuous self-education and interesting communication. Studies of social expression as an important factor influencing the formation of public consciousness should open up new facets of rational and emotional media broadcasting; to trace physical and psychological reactions to communicative mimicry in the media. Speech mimicry as one of the methods of disguise is increasingly becoming a dangerous factor in manipulating the media. Mimicry is an unprincipled adaptation to the surrounding social conditions; one of the most famous examples of an animal characterized by mimicry (change of protective color and shape) is a chameleon. In a figurative sense, chameleons are called adaptive journalists. Observations show that mimicry in politics is to some extent a kind of game that, like every game, is always conditional and artificial.

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