Signal processing using cellular neural networks
Journal of VLSI Signal Processing Systems - Parallel processing on VLSI arrays
Exponential stability of continuous-time and discrete-time cellular neural networks with delays
Applied Mathematics and Computation
Controlling chaos in a chaotic neural network
Neural Networks
Sliding mode observers for fault detection and isolation
Automatica (Journal of IFAC)
Robust adaptive control of a class of nonlinear systems with unknown dead-zone
Automatica (Journal of IFAC)
Robust adaptive control of nonlinear systems with unknown time delays
Automatica (Journal of IFAC)
Robust control of a class of neural networks with bounded uncertainties and time-varying delays
Computers & Mathematics with Applications
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This paper investigates the stabilization problem for uncertain cellular neural networks (CNNs) subject to time-varying delays and dead-zone input. On the basis of Lyapunov stability theory, a memoryless decentralized feedback control law is derived for guaranteeing global exponential stability of the system. The main results illustrate that the derived control law does not impose restriction on the derivative of the time-varying delays and can be applied to stabilizing the uncertain CNNs with time-varying delays and dead-zone input. An illustrative example is given to justify the validity and feasibility of the proposed control scheme.