This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form. The studied systems are composed of N subsystems in pure feedback structure and the interconnection terms are contained in ever...
This paper investigates the asymptotical stability problem for a class of neutral type neural networks with mixed time-varying delays. The system not only has time-varying discrete delay, but also distributed delay, which has never been discussed in ...
Neural networks : the official journal of the International Neural Network Society
Mar 30, 2015
It is a fundamental question how our brain performs a given motor task in a real-time fashion with the slow sensorimotor system. Computational theory proposed an influential idea of feed-forward control, but it has mainly treated the case that the mo...
Neural networks : the official journal of the International Neural Network Society
Mar 27, 2015
The urgent problem of impulsive moments which cannot be determined in advance brings new challenges beyond the conventional impulsive systems theory. In order to solve this problem, the novel concept of impulsive time window is proposed in this paper...
IEEE transactions on neural networks and learning systems
Mar 18, 2015
The output feedback-based near-optimal regulation of uncertain and quantized nonlinear discrete-time systems in affine form with control constraint over finite horizon is addressed in this paper. First, the effect of input constraint is handled using...
A general scheme to realize a perceptron for hardware neural networks is presented, where multiple interconnections are achieved by a superposition of Schrödinger waves. Spatially patterned potentials process information by coupling different points ...
IEEE transactions on neural networks and learning systems
Mar 16, 2015
High-gain observers have been extensively applied to construct output-feedback adaptive neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under a nonlinear separation principle. Yet due to static-gain and linear pr...
Journal of computational neuroscience
Mar 13, 2015
Granger causality (GC) analysis has emerged as a powerful analytical method for estimating the causal relationship among various types of neural activity data. However, two problems remain not very clear and further researches are needed: (1) The GC ...
Computational intelligence and neuroscience
Mar 8, 2015
A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbati...
IEEE transactions on neural networks and learning systems
Mar 5, 2015
This paper develops an adaptive robust output feedback control scheme for dynamically positioned ships with unavailable velocities and unknown dynamic parameters in an unknown time-variant disturbance environment. The controller is designed by incorp...