Dynamics of BAM neural networks with mixed delays and leakage time‐varying delays in the weighted pseudo–almost periodic on time‐space scales

Abstract

Bidirectional associative memory models are 2‐layer heteroassociative networks. In this work, we prove the existence and the global exponential stability of the unique weighted pseudo–almost periodic solution of bidirectional associative memory neural networks with mixed time‐varying delays and leakage time‐varying delays on time‐space scales. Some sufficient conditions are given for the existence, the convergence, and the global exponential stability of the weighted pseudo–almost periodic solution by using fixed‐point theorem and differential inequality techniques. The results of this paper complement the previous outcomes. An example is given to show the effectiveness of the derived results via computer simulations.

A generalized delta derivative on time scale with applications

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Almost anti-periodic solution of inertial neural networks model on time scales

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Existence and Global Attractivity of Pseudo Almost Periodic Solutions for Clifford-Valued Fuzzy Neural Networks with Proportional Delays

“…In addition, almost periodic oscillation and pseudo almost periodic oscillation are important dynamics of neural networks. Many authors have studied the existence and stability of almost periodic solutions [5,13] and pseudo almost periodic solutions [22][23][24][25][26] of neural networks, including stochastic neural networks [27] and fuzzy neural networks [28,29].…”