Paper Title:
A Special Criteria to Globally Exponentially Stability for Discrete-Time Recurrent Neural Networks
  Abstract

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, W. G. Wu, X. Yin, "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
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