A5035993926- Neural Networks Stability and Synchronization
- Advanced Memory and Neural Computing
- Neural Networks and Applications
- Stability and Control of Uncertain Systems
- Matrix Theory and Algorithms
- Spectral Theory in Mathematical Physics
- stochastic dynamics and bifurcation
- Distributed Control Multi-Agent Systems
- Elasticity and Wave Propagation
- Nonlinear Dynamics and Pattern Formation
- Control and Stability of Dynamical Systems
- Cooperative Communication and Network Coding
- Stability and Controllability of Differential Equations
- Machine Learning and ELM
- Gene Regulatory Network Analysis
- Neural dynamics and brain function
- Advanced Control Systems Design
- Microgrid Control and Optimization
- Graph Labeling and Dimension Problems
- Frequency Control in Power Systems
- Bacterial Genetics and Biotechnology
- Control Systems and Identification
- Gait Recognition and Analysis
- Smart Grid Energy Management
- thermodynamics and calorimetric analyses
Gandhigram Rural Institute
2016-2025
East Asia School of Theology
2021
UCSI University
2021
Maejo University
2021
Kunsan National University
2019
ABSTRACT In this article, exponential quasi‐synchronization of nonidentical discrete‐time complex‐valued neural networks (CVNNs) is investigated in the sense simultaneous existence parameter mismatches. Under memory‐based state‐feedback controller, CVNNs examined directly via nondecomposition approach by introducing parameter‐dependent reciprocal convex matrix inequality. To obtain less conservatism, an augmented Lyapunov–Krasovskii functional with delay‐product‐type term constructed which...
This paper focuses on the dynamical behavior for a class of memristor-based bidirectional associative memory neural networks (BAMNNs) with additive time-varying delays in discrete-time case. The necessity proposed problem is to design proper state estimator such that dynamics corresponding estimation error exponentially stable prescribed decay rate. By constructing an appropriate Lyapunov-Krasovskii functional (LKF) and utilizing Cauchy-Schwartz-based summation inequality, delay-dependent...
Summary In this paper, the problem of dissipativity and passivity analysis is investigated for discrete‐time complex‐valued neural networks with time‐varying delays. Both leakage discrete delays have been considered. By constructing a suitable Lyapunov–Krasovskii functional by using discretized Jensen's inequality approach, sufficient conditions established to guarantee ( Q , S R ) − γ addressed networks. These are derived in terms linear matrix inequalities (LMIs), which can be checked...
In this paper, we investigate the dissipativity and passivity of Markovian jump stochastic neural networks involving two additive time-varying delays. Using a Lyapunov-Krasovskii functional with triple quadruple integral terms, obtain delay-dependent criteria for system. generalized Finsler lemma (GFL), set slack variables special structure are introduced to reduce design conservatism. The depend on upper bounds discrete delay its derivative given in terms linear matrix inequalities, which...
In this article, we consider the problem of robust dissipativity and passivity analysis for a class general discrete‐time recurrent neural networks (NNs) with time‐varying delays. The NN under consideration is subject to norm bounded parameter uncertainties. By latest free‐weighting matrix method, an appropriate Lyapunov–Krasovskii functional using stochastic technique sufficient condition established ensure that NNs strictly ‐dissipative. derived conditions are presented in terms linear...