Stability of Complex-Valued Recurrent Neural Networks With Time-Delays | IEEE Journals & Magazine | IEEE Xplore

Stability of Complex-Valued Recurrent Neural Networks With Time-Delays


Abstract:

This brief points out two mistakes in a recently published paper on complex-valued recurrent neural networks (RNNs). Moreover, a new condition for the complex-valued acti...Show More

Abstract:

This brief points out two mistakes in a recently published paper on complex-valued recurrent neural networks (RNNs). Moreover, a new condition for the complex-valued activation function is presented, which is less conservative than the Lipschitz condition that is widely assumed in the literature. Based on the new condition and linear matrix inequality, some new criteria to ensure the existence, uniqueness, and globally asymptotical stability of the equilibrium point of complex-valued RNNs with time delays are established. A numerical example is given to illustrate the effectiveness of the theoretical results.
Published in: IEEE Transactions on Neural Networks and Learning Systems ( Volume: 25, Issue: 9, September 2014)
Page(s): 1709 - 1713
Date of Publication: 02 January 2014

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