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Artykuły w czasopismach na temat "Nonlinear adaptive models"

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Shapiro, Arnold F., and R. Paul Gorman. "Implementing adaptive nonlinear models." Insurance: Mathematics and Economics 26, no. 2-3 (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 (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 (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 (2005): 63–83. http://dx.doi.org/10.1016/j.jspi.2004.02.020.

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Annaswamy, A. M., C. Thanomsat, N. Mehta, and Ai-Poh Loh. "Applications of Adaptive Controllers to Systems With Nonlinear Parametrization." Journal of Dynamic Systems, Measurement, and Control 120, no. 4 (1998): 477–87. http://dx.doi.org/10.1115/1.2801489.

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Nonlinear parametrizations occur in dynamic models of several complex engineering problems. The theory of adaptive estimation and control has been applicable, by and large, to problems where parameters appear linearly. We have recently developed an adaptive controller that is capable of estimating parameters that appear nonlinearly in dynamic systems in a stable manner. In this paper, we present this algorithm and its applicability to two problems, temperature regulation in chemical reactors and precise positioning using magnetic bearings both of which contain nonlinear parametrizations. It is
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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 (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 (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 (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 (2000): 1093–105. http://dx.doi.org/10.1016/s0967-0661(00)00059-9.

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Rozprawy doktorskie na temat "Nonlinear adaptive models"

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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 o
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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 E
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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
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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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Książki na temat "Nonlinear adaptive models"

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

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Nassirharand, Amir. Computer-aided nonlinear control system design: Using describing function models. 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. Alfred-Wegener-Institut für Polar- und Meeresforschung, 2005.

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

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

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

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Luo, W. Adaptive model selection and estimation for nonlinear systems using a sliding data window. 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. 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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Części książek na temat "Nonlinear adaptive models"

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Zhang, Heping. "Mixed-Effects Multivariate Adaptive Splines Models." In Nonlinear Estimation and Classification. 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. 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. 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. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04921-7_8.

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Kunoth, Angela, Mathias Oster, and Reinhold Schneider. "Towards Continuous Mathematical Models for the Analysis of Classes of Deep Neural Networks." In Multiscale, Nonlinear and Adaptive Approximation II. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-75802-7_17.

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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. 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. 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. 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. 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. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16776-8_7.

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Streszczenia konferencji na temat "Nonlinear adaptive models"

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Al-Sudany, Huda Naji, and Béla Lantos. "Adaptive Obstacle Avoidance of UAV Leader/Followers with Nonlinear Logarithm Quaternion Control." In 2024 28th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2024. http://dx.doi.org/10.1109/mmar62187.2024.10680784.

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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
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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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Bray, Andrew, and Kadriye Merve Dogan. "Model Reference Adaptive Control of Uncertain Over-Actuated Nonlinear Systems With Nonlinear Reference Models." In AIAA SCITECH 2025 Forum. American Institute of Aeronautics and Astronautics, 2025. https://doi.org/10.2514/6.2025-2463.

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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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Shadaei, Maral, Saskia A. Putri, Faegheh Moazeni, and Javad Khazaei. "Microgrid Power Sharing: Adaptive vs. Nonlinear Predictive Models." In 2024 12th International Conference on Smart Grid (icSmartGrid). IEEE, 2024. http://dx.doi.org/10.1109/icsmartgrid61824.2024.10578193.

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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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Raporty organizacyjne na temat "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. SAE International, 2005. http://dx.doi.org/10.4271/2005-08-0423.

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Nobile, F., Q. Ayoul-Guilmard, S. Ganesh, et al. 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 t
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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. Pipeline Research Council International, Inc. (PRCI), 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 l
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Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, 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. Th
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