Noise-Tolerant Zeroing Neural Network for Solving Non-Stationary Lyapunov Equation

MATLAB Simulation and Comparison of Zhang Neural Network and Gradient Neural Network for Time-Varying Lyapunov Equation Solving

This paper presents a new kind of recurrent neural network proposed by Zhang et al. for solving online Lyapunov equation with time-varying coefficient matrices. Global exponential convergence could be achieved by such a recurrent neural network when solving the timevarying problems in comparison with gradient neural networks (GNN). MATLAB simulation of both neural networks for the real-time sol...

Iterative methods for solving non linear Fokker-Planck equation

A Recurrent Neural Network Model for Solving Linear Semidefinite Programming

In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs). SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations. Then a recurrent neural network...

A generalized ABFT technique using a fault tolerant neural network

In this paper we first show that standard BP algorithm cannot yeild to a uniform information distribution over the neural network architecture. A measure of sensitivity is defined to evaluate fault tolerance of neural network and then we show that the sensitivity of a link is closely related to the amount of information passes through it. Based on this assumption, we prove that the distribu...

A New Non-Autonomous Chaotic Neural Network for Solving TSP

In this paper we propose a new chaotic noise injection strategy into the Hopfield network which belongs to a general class of chaotic neural networks called "nonautonomous network". The objective of this method is to inject noise into the neurons based on the history of dynamics of their neighbor neurons. The measure of adjacency which is a criterion for definition of neighborhood, is based on ...