A Special Criteria to Globally Exponentially Stability for Discrete-Time Recurrent Neural Networks

Abstract:

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On average, each of the 1011 neurons has 1000 synaptic connections with other neurons in reality. In order to simulate a biological genuine model, the stability of a special discrete-time recurrent neural networks model that every neuron only has one input neuron is considered. And a main result is obtained. It provides some theoretical basis for the application.

Info:

Periodical:

Advanced Materials Research (Volumes 181-182)

Edited by:

Qi Luo and Yuanzhi Wang

Pages:

293-298

DOI:

10.4028/www.scientific.net/AMR.181-182.293

Citation:

J. M. Yuan et al., "A Special Criteria to Globally Exponentially Stability for Discrete-Time Recurrent Neural Networks", Advanced Materials Research, Vols. 181-182, pp. 293-298, 2011

Online since:

January 2011

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Price:

$35.00

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