Contents
1. Introduction
1.1 Research Significance of Complex-Valued Neural Networks Systems
1.2 History of Complex-Valued Neural Networks Systems
1.3 Book Organization
2. Stability Analysis of Delayed Complex-Valued Neural Networks Systems
2.1 Introduction
2.2 Problem Formulation
2.3 Stability Analysis Based on Separable Method
2.4 Further Stability Analysis Based on Separable Method
2.5 Stability Analysis Based on Nonseparable Method
2.6 Illustrative Examples
2.7 Conclusion and Notes
3. Further Behavior Analysis about Stability and Hopf Bifurcation
3.1 Introduction
3.2 Problem Formulation
3.3 Stability Result
3.4 Hopf Bifurcation Results
3.5 Illustrative Examples
3.6 Conclusion
4. Stability Analysis Based on Nonlinear Measure Approach
4.1 Introduction
4.2 Problem Formulation
4.3 Sufficient Condition to Ensure the Existence and Uniqueness of the Equilibrium Point
4.4 Finite-Time Stability Result
4.5 Illustrative Examples
4.6 Conclusion
5. Lagrange Exponential Stability for Delayed Complex-Valued Neural Networks Systems
5.1 Introduction
5.2 Problem Formulation
5.3 Sufficient Criteria Based on Algebraic Structure
5.4 Sufficient Condition in Terms of LMI
5.5 Illustrative Examples
5.6 Conclusion
6. Synchronization Control: Nonseparable Case
6.1 Introduction
6.2 Problem Formulation
6.3 Synchronization Result for Delayed Complex-Valued Inertial Neural Networks
6.4 Illustrative Example
6.5 Conclusion
7. Anti-Synchronization Control: Nonseparable Case
7.1 Introduction
7.2 Problem Formulation
7.3 Anti-Synchronization Result for Delayed Complex-Valued Inertial Neural Networks
7.4 Anti-Synchronization Result for Delayed Complex-Valued Neural Networks
7.5 Illustrative Examples
7.6 Conclusion
8. Anti-Synchronization Control: Separable Case
8.1 Introduction
8.2 Problem Formulation
8.3 Anti-Synchronization Result for Delayed Complex-Valued Neural Networks
8.4 Anti-Synchronization Result for Delayed Complex-Valued Bidirectional Associative Memory Neural Networks
8.5 Illustrative Examples
8.6 Conclusion
9. Finite/Fixed-Time Synchronization Control
9.1 Introduction
9.2 Problem Formulation
9.3 Finite-Time Synchronization Result
9.4 Fixed-Time Synchronization Result
9.5 Illustrative Examples
10. Fixed-Time Pinning Synchronization and Adaptive Synchronization
10.1 Introduction
10.2 Problem Formulation
10.3 Results for Delayed Complex-Valued Inertial Neural Networks
10.4 Results for Delayed Complex-Valued BAM Neural Networks
10.5 Illustrative Examples
10.6 Conclusion
References
Index