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  4. Passivity analysis of multiple time-varying time delayed complex variable neural networks in finite-time

Passivity analysis of multiple time-varying time delayed complex variable neural networks in finite-time

MMC.
2021;
Volume 8, Number 4
: pp. 842–854
https://doi.org/10.23939/mmc2021.04.842
Received: November 01, 2021
Accepted: November 29, 2021

Mathematical Modeling and Computing, Vol. 8, No. 4, pp. 842–854 (2021)

Authors:
  1. N. Jayanthi
  2. R. Santhakumari
1
Government Arts College, Coimbatore, India
2
Government Arts College, Coimbatore, India; Sri Ramakrishna College of Arts and Science, Coimbatore, India

In this article, we investigate the problem of finite-time passivity for the complex-valued neural networks (CVNNs) with multiple time-varying delays.  To begin, many definitions relevant to the finite-time passivity of CVNNs are provided; then the suitable control inputs are designed to guarantee the class of CVNNs are finite-time passive.  In the meantime, some sufficient conditions of linear matrix inequalities (LMIs) are derived by using inequalities techniques and Lyapunov stability theory.  Finally, a numerical example is presented to illustrate the usefulness of the theoretical results.

passivity
finite-time passivity
complex-valued neural networks
time-varying delays
Lyapunov functional
linear matrix inequality
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