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<div>1. Introduction.- 2. Stability Analysis of Delayed Complex-Valued Neural Networks Systems.- 3. Further Behavior Analysis about Stability and Hopf Bifurcation.- 4. Stability Analysis Based on Nonlinear Measure Approach.- 5. Lagrange Exponential Stability for Delayed Complex-Valued Neural Networks Systems .- 6. Synchronization Control: Nonseparable Case.- 7. Anti-Synchronization Control: Nonseparable Case.- 8. Anti-Synchronization Control: Separable Case.- 9. Finite/Fixed-Time Synchronization Control.- 10. Fixed-Time Pinning Synchronization and Adaptive Synchronization.</div><div><br></div><div><br></div>

<div><div><div><div>Ziye Zhang received the B.Sc. degree in mathematics from Yantai University, Yantai, China, in 2002, the M.Sc. degree in mathematics from Lanzhou University, Lanzhou, China, in 2005, and the Ph.D. degree from the Institute of Complexity Science, Qingdao University, Qingdao, China, in 2015. She is currently Associate Professor with the College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China. Her current research interests include systems analysis, fuzzy control, filter design, and neural networks.</div><div><br></div><div>Zhen Wang is currently Professor at College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China. He received Ph.D. degree from School of Automation, Nanjing University of Science and Technology, China, in 2013.</div><div><br></div><div>Jian Chen is Associate Professor at School of information and Control Engineering, Qingdao University of Technology, Qingdao, China. She received her Ph.D. degree from Institute of Complexity Science, Qingdao University, in 2017. Her research interest includes systems analysis and control.</div><div><br></div><div>Chong Lin is Professor at Institute of Complexity Science, Qingdao University, China. He received Ph.D. from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, in 1999.</div></div></div></div>

<div>This book provides up-to-date developments in the stability analysis and (anti-)synchronization control area for complex-valued neural networks systems with time delay. It brings out the characteristic systematism in them and points out further insight to solve relevant problems. It presents a comprehensive, up-to-date, and detailed treatment of dynamical behaviors including stability analysis and (anti-)synchronization control. The materials included in the book are mainly based on the recent research work carried on by the authors in this domain.&nbsp;</div><div><br></div><div>The book is a useful reference for all those from senior undergraduates, graduate students, to senior researchers interested in or working with control theory, applied mathematics, system analysis and integration, automation, nonlinear science, computer and other related fields, especially those relevant scientific and technical workers in the research of complex-valued neural network systems, dynamic systems, and intelligent control theory.</div><div><br></div>

Provides more complete interpretation of dynamical behaviors for complex-valued neural networks systems with time delay Considers anti-synchronization control, finite/fixed-time synchronization, etc., from the point of cost saving Diversifies stability forms including asymptotic stability, finite-time stability, and Lagrange exponential stability