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Nonlinear Dynamics

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Stability criteria for recurrent neural networks with time-varying delay based on secondary delay partitioning method.

IEEE transactions on neural networks and learning systems
A secondary delay partitioning method is proposed to study the stability problem for a class of recurrent neural networks (RNNs) with time-varying delay. The total interval of the time-varying delay is first divided into two parts, and then each part...

Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption.

IEEE transactions on neural networks and learning systems
This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the outp...

Energy-to-peak state estimation for Markov jump RNNs with time-varying delays via nonsynchronous filter with nonstationary mode transitions.

IEEE transactions on neural networks and learning systems
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of n...

Adaptive control of uncertain nonaffine nonlinear systems with input saturation using neural networks.

IEEE transactions on neural networks and learning systems
This paper presents a tracking control methodology for a class of uncertain nonlinear systems subject to input saturation constraint and external disturbances. Unlike most previous approaches on saturated systems, which assumed affine nonlinear syste...

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

Neural networks : the official journal of the International Neural Network Society
Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibl...

Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation.

IEEE transactions on neural networks and learning systems
In this paper, a dynamic surface control (DSC) scheme is proposed for a class of uncertain strict-feedback nonlinear systems in the presence of input saturation and unknown external disturbance. The radial basis function neural network (RBFNN) is emp...

Finite-time synchronization control of a class of memristor-based recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive-response concept, differential inclusions theory, and Lyapunov functional method, we establish several sufficient con...

Circuit design and exponential stabilization of memristive neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the problem of circuit design and global exponential stabilization of memristive neural networks with time-varying delays and general activation functions. Based on the Lyapunov-Krasovskii functional method and free weighting mat...

Approximation-Based Adaptive Tracking Control for MIMO Nonlinear Systems With Input Saturation.

IEEE transactions on cybernetics
In this paper, an approximation-based adaptive tracking control approach is proposed for a class of multiinput multioutput nonlinear systems. Based on the method of neural network, a novel adaptive controller is designed via backstepping design proce...

Latching chains in K-nearest-neighbor and modular small-world networks.

Network (Bristol, England)
Latching dynamics retrieve pattern sequences successively by neural adaption and pattern correlation. We have previously proposed a modular latching chain model in Song et al. (2014) to better accommodate the structured transitions in the brain. Diff...