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This book presents the novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols.
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This book presents the novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 241
- Erscheinungstermin: 18. Dezember 2023
- Englisch
- Abmessung: 234mm x 156mm x 16mm
- Gewicht: 540g
- ISBN-13: 9781032555621
- ISBN-10: 1032555629
- Artikelnr.: 68712332
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 241
- Erscheinungstermin: 18. Dezember 2023
- Englisch
- Abmessung: 234mm x 156mm x 16mm
- Gewicht: 540g
- ISBN-13: 9781032555621
- ISBN-10: 1032555629
- Artikelnr.: 68712332
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
Yuxuan Shen received the PhD degree in control science and engineering from the Donghua University, Shanghai, China, in 2020.From June 2018 to September 2018, he was a Research Assistant in the Texas A&M University at Qatar, Doha, Qatar. From November 2018 to November 2019, he was a Visiting Scholar with the Department of Computer Science, Brunel University London, London, United Kingdom. From July 2020 to August 2021, he worked as a Lecturer in the Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, China where he was promoted to an Associate Professor in September 2021. He has published over 30 papers in refereed international journals. His research interests include optimal filtering, multi-rate systems, communication protocols as well as fault detection. He is a very active reviewer for several international journals. He was an outstanding reviewer for Neurocomputing in 2017 and for Asian Journal of Control in 2020. Zidong Wang is Professor of Dynamical Systems and Computing at Brunel University London, London, United Kingdom. He was born in 1966 in Yangzhou, Jiangsu, China. He received the BSc degree in Mathematics in 1986 from Suzhou University, Suzhou, the MSc degree in Applied Mathematics in 1990 and the PhD degree in Electrical and Computer Engineering in 1994, both from Nanjing University of Science and Technology, Nanjing.He was appointed as Lecturer in 1990 and Associate Professor in 1994 at Nanjing University of Science and Technology. From January 1997 to December 1998, he was an Alexander von Humboldt research fellow with the Control Engineering Laboratory, Ruhr-University Bochum, Germany. From January 1999 to February 2001, he was a Lecturer with the Department of Mathematics, University of Kaiserslautern, Germany. From March 2001 to July 2002, he was a University Senior Research Fellow with the School of Mathematical and Information Sciences, Coventry University, United Kingdom. In August 2002, he joined the Department of Computer Science, Brunel University London, United Kingdom, as a Lecturer, and was then promoted to a Reader in September 2003 and to a Chair Professor in July 2007.Professor Wang's research interests include dynamical systems, signal processing, bioinformatics, control theory and applications. He has published more than 600 papers in refereed international journals. He was awarded the Humboldt research fellowship in 1996 from Alexander von Humboldt Foundation, the JSPS Research Fellowship in 1998 from Japan Society for the Promotion of Science, and the William Mong Visiting Research Fellowship in 2002 from the University of Hong Kong. He was a recipient of the State Natural Science Award from the State Council of China in2014 and the Outstanding Science and Technology Development Awards (once in 2005 and twice in 1997) from the National Education Committee of China.Professor Wang is currently serving or has served as the Editor-in-Chief for International Journal of Systems Science, the Editor-in-Chief for Neurocomputing, Executive Editor for Systems Science and Control Engineering, Subject Editor for Journal of The Franklin Institute, an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, IEEE Transactions on Systems, Man, and Cybernetics - Systems, Asian Journal of Control, Science China Information Sciences, IEEE/CAA Journal of Automatica Sinica, Control Theory and Technology, an Action Editor for Neural Networks, an Editorial Board Member for Information Fusion, IET Control Theory & Applications, Complexity, International Journal of Systems Science, Neurocomputing, International Journal of General Systems, Studies in Autonomic, Data-driven and Industrial Computing, and a member of the Conference Editorial Board for the IEEE Control Systems Society. He served as an Associate Editor for IEEE Transactions on Neural Networks, IEEE Transactions on Systems, Man, and Cybernetics - Part C, IEEE Transactions on Signal Processing, Circuits, Systems & Signal Processing, and an Editorial Board Member for International Journal of Computer Mathematics.Professor Wang is a Member of the Academia Europaea (section of Physics and Engineering Sciences), a Fellow of the IEEE (for contributions to networked control and complex networks), a Fellow of the Chinese Association of Automation, a Member of the IEEE Press Editorial Board, a Member of the EPSRC Peer Review College of the UK, a Fellow of the Royal Statistical Society, a member of program committee for many international conferences, and a very active reviewer for many international journals. He was nominated an appreciated reviewer for IEEE Transactions on Signal Processing in 2006-2008 and 2011, an appreciated reviewer for IEEE Transactions on Intelligent Transportation Systems in 2008, an outstanding reviewer for IEEE Transactions on Automatic Control in 2004 and for the journal Automatica in 2000. Hongli Dong received the PhD degree in control science and engineering from the Harbin Institute of Technology, Harbin, China, in 2012.She was a Research Assistant with the Department of Applied Mathematics, City University of Hong Kong, Hong Kong, from 2009 to 2010 and with the Department of Mechanical Engineering, University of Hong Kong, Hong Kong, from 2010 to 2011. From 2011 to 2012, she was a Visiting Scholar with the Department of Information Systems and Computing, Brunel University London, London, United Kingdom. From 2012 to 2014, she was an Alexander von Humboldt Research Fellow with the University of Duisburg-Essen, Duisburg, Germany. She is currently a Professor with the Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, China, where she is also the Director of theHeilongjiang Provincial Key Laboratory of Networking and Intelligent Control. Her current research interests include robust control and networked control systems.Dr. Dong is a very active reviewer for many international journals.
Chapter 1 Introduction Chapter 2 Non-Fragile H
Filtering for Multi-Rate Time-Delayed Sys
tems over Sensor Networks Chapter 3 H
Filtering for Multi-Rate Artificial Neural Networks with Integral Measurements Chapter 4 Recursive State Estimation for Multi-Rate Systems with Sen
sor Resolutions Chapter 5 Minimum-Variance State and Fault Estimation for Multi
Rate Systems with Dynamical Bias Chapter 6 H
Filtering for Multi-Rate Systems under p-Persistent CS
MA Protocol Chapter 7 l2-l
State Estimation for Artificial Neural Networks under High-Rate Channels with Round-Robin Protoco Chapter 8 Recursive State Estimation for Multi-Rate Systems with Dis
tributed Time-Delays under Round-Robin Protocol Chapter 9 Fusion Estimation for Multi-Rate Linear Repetitive Process
es under Weighted Try-Once-Discard Protocol Chapter 10 Outlier-Resistant Recursive Filtering for Multi-Rate Systems under Weighted Try-Once-Discard Protocol Chapter 11 Dynamic Event-Based Recursive Filtering for Multi-Rate Systems with Integral Measurements over Sensor Networks
Filtering for Multi-Rate Time-Delayed Sys
tems over Sensor Networks Chapter 3 H
Filtering for Multi-Rate Artificial Neural Networks with Integral Measurements Chapter 4 Recursive State Estimation for Multi-Rate Systems with Sen
sor Resolutions Chapter 5 Minimum-Variance State and Fault Estimation for Multi
Rate Systems with Dynamical Bias Chapter 6 H
Filtering for Multi-Rate Systems under p-Persistent CS
MA Protocol Chapter 7 l2-l
State Estimation for Artificial Neural Networks under High-Rate Channels with Round-Robin Protoco Chapter 8 Recursive State Estimation for Multi-Rate Systems with Dis
tributed Time-Delays under Round-Robin Protocol Chapter 9 Fusion Estimation for Multi-Rate Linear Repetitive Process
es under Weighted Try-Once-Discard Protocol Chapter 10 Outlier-Resistant Recursive Filtering for Multi-Rate Systems under Weighted Try-Once-Discard Protocol Chapter 11 Dynamic Event-Based Recursive Filtering for Multi-Rate Systems with Integral Measurements over Sensor Networks
Chapter 1 Introduction Chapter 2 Non-Fragile H
Filtering for Multi-Rate Time-Delayed Sys
tems over Sensor Networks Chapter 3 H
Filtering for Multi-Rate Artificial Neural Networks with Integral Measurements Chapter 4 Recursive State Estimation for Multi-Rate Systems with Sen
sor Resolutions Chapter 5 Minimum-Variance State and Fault Estimation for Multi
Rate Systems with Dynamical Bias Chapter 6 H
Filtering for Multi-Rate Systems under p-Persistent CS
MA Protocol Chapter 7 l2-l
State Estimation for Artificial Neural Networks under High-Rate Channels with Round-Robin Protoco Chapter 8 Recursive State Estimation for Multi-Rate Systems with Dis
tributed Time-Delays under Round-Robin Protocol Chapter 9 Fusion Estimation for Multi-Rate Linear Repetitive Process
es under Weighted Try-Once-Discard Protocol Chapter 10 Outlier-Resistant Recursive Filtering for Multi-Rate Systems under Weighted Try-Once-Discard Protocol Chapter 11 Dynamic Event-Based Recursive Filtering for Multi-Rate Systems with Integral Measurements over Sensor Networks
Filtering for Multi-Rate Time-Delayed Sys
tems over Sensor Networks Chapter 3 H
Filtering for Multi-Rate Artificial Neural Networks with Integral Measurements Chapter 4 Recursive State Estimation for Multi-Rate Systems with Sen
sor Resolutions Chapter 5 Minimum-Variance State and Fault Estimation for Multi
Rate Systems with Dynamical Bias Chapter 6 H
Filtering for Multi-Rate Systems under p-Persistent CS
MA Protocol Chapter 7 l2-l
State Estimation for Artificial Neural Networks under High-Rate Channels with Round-Robin Protoco Chapter 8 Recursive State Estimation for Multi-Rate Systems with Dis
tributed Time-Delays under Round-Robin Protocol Chapter 9 Fusion Estimation for Multi-Rate Linear Repetitive Process
es under Weighted Try-Once-Discard Protocol Chapter 10 Outlier-Resistant Recursive Filtering for Multi-Rate Systems under Weighted Try-Once-Discard Protocol Chapter 11 Dynamic Event-Based Recursive Filtering for Multi-Rate Systems with Integral Measurements over Sensor Networks