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Global Stability of Complex-Valued Neural Networks on Time Scales

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Abstract

In this paper, activation dynamics of complex-valued neural networks are studied on general time scales. Besides presenting conditions guaranteeing the existence of a unique equilibrium pattern, its global exponential stability is discussed. Some numerical examples for different time scales are given in order to highlight the results.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO, 65409-0020, USA

    Martin Bohner & V. Sree Hari Rao

  2. Department of Mathematics, Marshall University, Huntington, WV, 25755-2560, USA

    Suman Sanyal

Authors
  1. Martin Bohner
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  2. V. Sree Hari Rao
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  3. Suman Sanyal
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Corresponding author

Correspondence to Suman Sanyal.

Additional information

V. Sree Hari Rao is on leave from Jawaharlal Nehru Technological University, Hyderabad 500 085, (A.P.), India.

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Bohner, M., Sree Hari Rao, V. & Sanyal, S. Global Stability of Complex-Valued Neural Networks on Time Scales. Differ Equ Dyn Syst 19, 3–11 (2011). https://doi.org/10.1007/s12591-010-0076-9

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  • DOI: https://doi.org/10.1007/s12591-010-0076-9

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