A New Sufficient Condition on the Complete Stability of a Class Cellular Neural Networks
Part of the
Lecture Notes in Computer Science
book series (LNCS, volume 3971)
In this paper, a sufficient condition is presented to ensure the complete stability of a cellular neural networks (CNNs) that output functions are a set of piecewise sigmoid nonlinear functions. The convergence theorem of the Gauss-Seidel method and Gauss-Seidel method, which is an iterative technique for solving a linear algebraic equation, plays an important role in our discussion.
KeywordsLinear Algebraic Equation Comparison Matrix Cellular Neural Network Zero Vector Iterative Technique
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