L∞ analysis and state-feedback control of Hopfield networks.

Stoica, Adriannmihail; Yaesh, Isaac · IEEE Trans Neural Netw Learn Syst · 2013

basic_science · Level V

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Abstract

A nonsymmetric version of Hopfield networks subject to bounded disturbances is considered. Such networks arise in the context of visuo-motor control loops and may, therefore, be used to mimic their complex behavior. In this brief, we adopt the Lur'e-Postnikov systems approach to analyze the induced L∞ gain of generalized Hopfield networks. A state-feedback control is then designed to accomplish the L∞-type performance for Hopfield networks. The results are illustrated through numerical examples.