Stability Analysis and State Estimation of Memristive Neural Networks

Liu, Hongjian/ Wang, Zidong/ Ma, Lifeng

ISBN 10: 1032037105 / ISBN 13: 9781032037103

Published by CRC Pr I Llc, 2021

About this Item

214 pages. 9.50x6.25x1.00 inches. In Stock.

Seller Inventory # x-1032037105

Bibliographic Details

• Title: Stability Analysis and State Estimation of Memristive Neural Networks
• Publisher: CRC Pr I Llc
• Publication Date: 2021
• Language: English
• ISBN 10: 1032037105
• ISBN 13: 9781032037103
• Binding: Hardcover
• Condition: Brand New
• Weight: 1.02 kilograms

About this title

Synopsis

In this book, the stability analysis and estimator design problems are discussed for delayed discrete-time memristive neural networks. In each chapter, the analysis problems are firstly considered, where the stability, synchronization and other performances (e.g., robustness, disturbances attenuation level) are investigated within a unified theoretical framework. In this stage, some novel notions are put forward to reflect the engineering practice. Then, the estimator design issues are discussed where sufficient conditions are derived to ensure the existence of the desired estimators with guaranteed performances. Finally, the theories and techniques developed in previous parts are applied to deal with some issues in several emerging research areas.

The book

• Unifies existing and emerging concepts concerning delayed discrete memristive neural networks with an emphasis on a variety of network-induced phenomena
• Captures recent advances of theories, techniques, and applications of delayed discrete memristive neural networks from a network-oriented perspective
• Provides a series of latest results in two popular yet interrelated areas, stability analysis and state estimation of neural networks
• Exploits a unified framework for analysis and synthesis by designing new tools and techniques in combination with conventional theories of systems science, control engineering and signal processing
• Gives simulation examples in each chapter to reflect the engineering practice

About the Author

Hongjian Liu is currently a Professor in the School of Mathematics and Physics, Anhui Polytechnic University, Wuhu, China. His current research interests include filtering theory, memristive neural networks and network communication systems. He is a very active reviewer for many international journals.

Zidong Wang is currently Professor of Dynamical Systems and Computing at Brunel University London in the United Kingdom. His research interests include dynamical systems, signal processing, bioinformatics, control theory and applications.

Lifeng Ma is currently a Professor with the School of Automation, Nanjing University of Science and Technology, Nanjing, China. His current research interests include nonlinear control and signal processing, variable structure control, distributed control and filtering, time-varying systems, and multi-agent systems.