This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined concept of stability, synchronization and consensus are adopted to provide a better explanation of the complex neural network. Researchers in the fields of dynamical systems, computer science, electrical engineering and mathematics will benefit from the discussions on complex systems. The book will also help readers to better understand the theory behind the control technique and its design.
This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined concept of stability, synchronization and consensus are adopted to provide a better explanation of the complex neural network. Researchers in the fields of dynamical systems, computer science, electrical engineering and mathematics will benefit from the discussions on complex systems. The book will also help readers to better understand the theory behind the control technique and its design.
Discusses the redefined concepts of stability, synchronization and consensus for complex neural networks Provides new insights into neural networks and their applications in electrical engineering Helps readers to understand the theory behind the control technique and its design Includes supplementary material: sn.pub/extras
Zhanshan Wang
Complex Neural Network Consensus of MAS Dynamical Stability Multi-agent System Multistability of Neural Network Neural Network Optimal Computation Power System Synchronization Stability complexity
“Each chapter is independent and self-contained and the book can be read randomly according to one's requirements. … This book should benefit researchers and senior graduate/post-graduate students interested in the study of dynamical systems, by providing different kinds of mathematical tools and techniques. … this book will definitely benefit readers, providing new insight into the area of neural networks in particular and dynamical systems in general, thereby enriching the literature.” (Ponnado Raja Sekhara Rao, Mathematical Reviews, April, 2017)
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