Affiliation:
1. City College, Kunming University of Science and Technology, Kunming, China
Abstract
A class of stochastic neural networks with discrete-time analogue is
investigated in this paper. By employing contraction mapping principle and
some stochastic analysis techniques, we establish some sufficient conditions
for mean boundedness, global attractivity and almost periodic sequence of
the model. An example and graphic illustrations are displayed to visually
expound the main contributions. The research techniques in this literature
are suitable for other stochastic models in science and engineering.
Publisher
National Library of Serbia
Cited by
1 articles.
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