Auswahl der wissenschaftlichen Literatur zum Thema „Stochastic algorithms parameters identification“
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Zeitschriftenartikel zum Thema "Stochastic algorithms parameters identification"
Zhang, Ce, Xiangxiang Meng und Yan Ji. „Parameter Estimation of Fractional Wiener Systems with the Application of Photovoltaic Cell Models“. Mathematics 11, Nr. 13 (30.06.2023): 2945. http://dx.doi.org/10.3390/math11132945.
Der volle Inhalt der QuelleJi, Yuejiang, und Lixin Lv. „Two Identification Methods for a Nonlinear Membership Function“. Complexity 2021 (30.04.2021): 1–7. http://dx.doi.org/10.1155/2021/5515888.
Der volle Inhalt der QuelleHu, Huiyi, Xiao Yongsong und Rui Ding. „Multi-Innovation Stochastic Gradient Identification Algorithm for Hammerstein Controlled Autoregressive Autoregressive Systems Based on the Key Term Separation Principle and on the Model Decomposition“. Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/596141.
Der volle Inhalt der QuelleOlama, Mohammed M., Kiran K. Jaladhi, Seddik M. Djouadi und Charalambos D. Charalambous. „Recursive Estimation and Identification of Time-Varying Long-Term Fading Channels“. Research Letters in Signal Processing 2007 (2007): 1–5. http://dx.doi.org/10.1155/2007/17206.
Der volle Inhalt der QuelleMa, Ping, und Lei Wang. „Partially Coupled Stochastic Gradient Estimation for Multivariate Equation-Error Systems“. Mathematics 10, Nr. 16 (16.08.2022): 2955. http://dx.doi.org/10.3390/math10162955.
Der volle Inhalt der QuelleTsyganov, Andrey, und Yulia Tsyganova. „SVD-Based Identification of Parameters of the Discrete-Time Stochastic Systems Models with Multiplicative and Additive Noises Using Metaheuristic Optimization“. Mathematics 11, Nr. 20 (15.10.2023): 4292. http://dx.doi.org/10.3390/math11204292.
Der volle Inhalt der QuelleKovacevic, Ivana, Branko Kovacevic und Zeljko Djurovic. „On strong consistency of a class of recursive stochastic Newton-Raphson type algorithms with application to robust linear dynamic system identification“. Facta universitatis - series: Electronics and Energetics 21, Nr. 1 (2008): 1–21. http://dx.doi.org/10.2298/fuee0801001k.
Der volle Inhalt der QuelleMaitre, Julien, Sébastien Gaboury, Bruno Bouchard und Abdenour Bouzouane. „A Black-Box Model for Estimation of the Induction Machine Parameters Based on Stochastic Algorithms“. International Journal of Monitoring and Surveillance Technologies Research 3, Nr. 3 (Juli 2015): 44–67. http://dx.doi.org/10.4018/ijmstr.2015070103.
Der volle Inhalt der QuelleHsu, Geesern, Andrew E. Yagle, Kenneth C. Ludema und Joel A. Levitt. „Modeling and Identification of Lubricated Polymer Friction Dynamics“. Journal of Dynamic Systems, Measurement, and Control 122, Nr. 1 (11.10.1996): 78–88. http://dx.doi.org/10.1115/1.482431.
Der volle Inhalt der QuelleKrasheninnikov, Viktor R., Yuliya E. Kuvayskova, Olga E. Malenova und Aleksey Y. Subbotin. „PSEUDOGRADIENT ALGORITHM FOR IDENTIFICATION OF DOUBLY STOCHASTIC CYLINDRICAL IMAGE“. Автоматизация процессов управления 2, Nr. 64 (2021): 56–65. http://dx.doi.org/10.35752/1991-2927-2021-2-64-56-65.
Der volle Inhalt der QuelleDissertationen zum Thema "Stochastic algorithms parameters identification"
Larsson, Erik. „Identification of stochastic continuous-time systems : algorithms, irregular sampling and Cramér-Rao bounds /“. Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3944.
Der volle Inhalt der QuelleKoenig, Guillaume. „Par vagues et marées : étude de la circulation hydrodynamique d’un lagon étroit de Nouvelle-Calédonie et identification des conditions aux bords à l’aide d’un algorithme stochastique“. Electronic Thesis or Diss., Aix-Marseille, 2021. http://www.theses.fr/2021AIXM0533.
Der volle Inhalt der QuelleIn this thesis, I have studied the hydrodynamics of the Ouano coral lagoon in NewCaledonia and implemented a novel parameter identification algorithm to do so.Wave-breaking and tides dominate the Ouano lagoon; I wanted to evaluate theirimpact on the lagoon flushing.Several studies have been done in the lagoon before. I rely on both their findings forthe circulation and their tools for the modeling, namely the CROCO ( Coastal RegionalOcean COmmunity model) of C. Chevalier. I also have used data collected in 2016 inthe lagoon. However, some uncertainties remained on the amount of water broughtby the tides and the wave-breaking in the lagoon. Also, the parametrization of thewave-breaking friction coefficient and the tidal boundary conditions in the numericalmodel was uncertain.I implemented and tested a tool to improve those parametrizations or other modelparameters. This tool was a stochastic parameter identification algorithm, the Simul-taneous Perturbations Stochastic Approximations (SPSA) algorithm.We first tested different variants of the algorithm in a controlled environment andwith a 1-D turbulence model. Then I have used this algorithm to identify boundaryconditions with a linear tidal model of the Ouano lagoon. Finally, I have used thealgorithm to study the impact of the wave-breaking on the measurement of tides inthe Ouano
Jenča, Pavol. „Identifikace parametrů elektrických motorů metodou podprostorů“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219678.
Der volle Inhalt der QuelleDebonos, Andreas A. „Estimation of non-linear ship roll parameters using stochastic identification techniques“. Thesis, University of Sussex, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295784.
Der volle Inhalt der QuelleAlamyal, Mohamoud Omran A. „Evaluation of stochastic optimisation algorithms for induction machine winding fault identification“. Thesis, University of Newcastle upon Tyne, 2013. http://hdl.handle.net/10443/1937.
Der volle Inhalt der QuelleZhou, Haiyan. „Stochastic Inverse Methods to Identify non-Gaussian Model Parameters in Heterogeneous Aquifers“. Doctoral thesis, Universitat Politècnica de València, 2011. http://hdl.handle.net/10251/12267.
Der volle Inhalt der QuelleZhou ., H. (2011). Stochastic Inverse Methods to Identify non-Gaussian Model Parameters in Heterogeneous Aquifers [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/12267
Palancia
Dong, Wei. „Identification of Electrical Parameters in A Power Network Using Genetic Algorithms and Transient Measurements“. Thesis, University of Nottingham, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.523043.
Der volle Inhalt der Quellevan, Wyk Hans-Werner. „A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems“. Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27635.
Der volle Inhalt der QuellePh. D.
Harth, Tobias [Verfasser]. „Identification of Material Parameters for Inelastic Constitutive Models : Stochastic Simulation and Design of Experiments / Tobias Harth“. Aachen : Shaker, 2003. http://d-nb.info/1179036204/34.
Der volle Inhalt der QuelleWong, king-fung, und 黃景峰. „Non-coding RNA identification along genome“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B4581949X.
Der volle Inhalt der QuelleBücher zum Thema "Stochastic algorithms parameters identification"
System identification with quantized observations. Boston: Birkhäuser, 2010.
Den vollen Inhalt der Quelle findenR, Kumar. A novel multistage estimation of the signal parameters of a possibly data-modulated sinusoid under very high dynamics. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1989.
Den vollen Inhalt der Quelle findenKamenskaya, Valentina, und Leonid Tomanov. The fractal-chaotic properties of cognitive processes: age. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1053569.
Der volle Inhalt der QuelleFarooqi, Zarreen H. H. Identification of stochastic systems with random parameters with particular reference to the recirculating lymphocytes in the immune system. 1986.
Den vollen Inhalt der Quelle findenLarsson, Erik. Identification of Stochastic Continuous-Time Systems: Algorithms, Irregular Sampling & Cramer-Rao Bounds (Uppsala Dissertations from the Faculty of Science & Technology, 52). Uppsala Universitet, 2003.
Den vollen Inhalt der Quelle findenZhang, Ji-Feng, Le Yi Wang und G. George Yin. System Identification with Quantized Observations. Birkhäuser, 2010.
Den vollen Inhalt der Quelle findenLeondes, Cornelius T. Control and Dynamic Systems: Advances in Theory and Applications : Advances in Algorithms and Computational Techniques in Dynamic Systems Control, P (Control and Dynamic Systems). Academic Press, 1989.
Den vollen Inhalt der Quelle findenAllen, Michael P., und Dominic J. Tildesley. Molecular dynamics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0003.
Der volle Inhalt der QuelleBuchteile zum Thema "Stochastic algorithms parameters identification"
Al-Ani, Tarik, und Yskander Hamam. „Parameters identification of a time-varying stochastic dynamic systems using Viterbi algorithm“. In System Modelling and Optimization, 567–73. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-0-387-34897-1_69.
Der volle Inhalt der QuelleBenveniste, Albert, Michel Métivier und Pierre Priouret. „Tracking Non-Stationary Parameters“. In Adaptive Algorithms and Stochastic Approximations, 120–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75894-2_5.
Der volle Inhalt der QuelleGuo, L., H. F. Chen und J. F. Zhang. „Identification of Stochastic Time-Varying Parameters“. In The IMA Volumes in Mathematics and its Applications, 211–23. New York, NY: Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4613-9296-5_12.
Der volle Inhalt der QuelleCao, Yi, Yuehui Chen und Yaou Zhao. „Stochastic System Identification by Evolutionary Algorithms“. In Bio-Inspired Computing and Applications, 247–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24553-4_34.
Der volle Inhalt der QuelleBoutalis, Yiannis, Dimitrios Theodoridis, Theodore Kottas und Manolis A. Christodoulou. „Adaptive Estimation Algorithms of FCN Parameters“. In System Identification and Adaptive Control, 215–49. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06364-5_9.
Der volle Inhalt der QuelleWang, Wei. „Generalized Extended Stochastic Gradient Algorithm Implemented Parameter Identification for Complex Multivariable-Systems“. In Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019), 663–73. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0474-7_62.
Der volle Inhalt der QuelleBellizzi, S., und R. Bouc. „Identification of the Hysteresis Parameters of a Nonlinear Vehicle Suspension Under Random Excitation“. In Nonlinear Stochastic Dynamic Engineering Systems, 467–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83334-2_34.
Der volle Inhalt der QuelleCascone, Dario, Giacomo Navarra, Maria Oliva und Francesco Lo Iacono. „Influence of User-Defined Parameters Using Stochastic Subspace Identification (SSI)“. In Lecture Notes in Mechanical Engineering, 1567–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41057-5_127.
Der volle Inhalt der QuelleHarth, Tobias, Jürgen Lehn und Franz Gustav Kollmann. „Identification of Material Parameters for Inelastic Constitutive Models: Stochastic Simulation“. In Deformation and Failure in Metallic Materials, 139–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36564-8_6.
Der volle Inhalt der Quellede la Higuera, Colin, und Franck Thollard. „Identification in the Limit with Probability One of Stochastic Deterministic Finite Automata“. In Grammatical Inference: Algorithms and Applications, 141–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-540-45257-7_12.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Stochastic algorithms parameters identification"
Chernyshov, Kirill R. „Extended stochastic approximation algorithms for systems parameters identification“. In IEEE EUROCON 2009 (EUROCON). IEEE, 2009. http://dx.doi.org/10.1109/eurcon.2009.5167742.
Der volle Inhalt der QuelleWang, Chunlin, Torodd Skjerve Nord und Guoyuan Li. „Automated Modal Parameters Identification During Ice-Structure Interactions“. In ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/omae2022-81075.
Der volle Inhalt der QuelleWade, S. „Comparison of stochastic and deterministic parameter identification algorithms for indirect vector control“. In IEE Colloquium on Vector Control and Direct Torque Control of Induction Motors. IEE, 1995. http://dx.doi.org/10.1049/ic:19951109.
Der volle Inhalt der QuelleHouili, Rabiaa, Mohamed Yacine Hammoudi, Abir Betka und Abdenacer Titaouine. „Stochastic optimization algorithms for parameter identification of three phase induction motors with experimental verification“. In 2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS). IEEE, 2023. http://dx.doi.org/10.1109/icaeccs56710.2023.10104526.
Der volle Inhalt der QuelleWang, S. Q., Y. T. Zhang und Y. X. Feng. „Comparative Study of Output-Based Modal Identification Methods Using Measured Signals From an Offshore Platform“. In ASME 2010 29th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/omae2010-20771.
Der volle Inhalt der QuelleBook, Joel M., und Samuel F. Asokanthan. „Modal Characterization of MEMS Switches via Output Only and Input/Output Identification Methods“. In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48888.
Der volle Inhalt der QuelleYang, Wenlong, Lei Li, Qiang Fu, Yao Teng, Shuqing Wang und Fushun Liu. „Identify Modal Parameters of a Real Offshore Platform From the Response Excited by Natural Ice Loading“. In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54821.
Der volle Inhalt der QuelleYin, Hao, He Xu, Yuhan Zhao und Feng Sun. „Fault Diagnosis of Control Valve Based on Fusion of Deep Learning and Elastic Weight Consolidation“. In BATH/ASME 2022 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/fpmc2022-89359.
Der volle Inhalt der QuelleYu, Shi Miao, Youngmok Ko, Han Hu, Jun Seo und Amy M. Bilton. „Optimization and System Identification of a Variable Pico-Scale Hydro Turbine for Pressure Regulation“. In ASME 2020 Power Conference collocated with the 2020 International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/power2020-16902.
Der volle Inhalt der QuelleCarassale, Luigi, Michela Marrè-Brunenghi und Stefano Patrone. „Modal Identification of Dynamically Coupled Bladed Disks in Run-Up Tests“. In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-57251.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Stochastic algorithms parameters identification"
Heeringa, Brent, und Tim Oates. Two Algorithms for Learning the Parameters of Stochastic Context-Free Grammars. Fort Belvoir, VA: Defense Technical Information Center, Januar 2001. http://dx.doi.org/10.21236/ada459920.
Der volle Inhalt der QuelleKuropiatnyk, D. I. Actuality of the problem of parametric identification of a mathematical model. [б. в.], Dezember 2018. http://dx.doi.org/10.31812/123456789/2885.
Der volle Inhalt der QuelleEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak und Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, Juli 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Der volle Inhalt der QuelleMiles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber und Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.
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