On global dissipativity of nonautonomous neural networks with multiple proportional delays

This brief addresses the problem of global dissipativity analysis of nonautonomous neural networks with multiple proportional delays. By using a novel constructive approach based on some comparison
techniques for differential inequalities, new explicit delay-independent
conditions are derived using M-matrix theory to ensure the existence of
generalized exponential attracting sets and the global dissipativity of the
system. The method presented in this brief is also utilized to derive a
generalized exponential estimate for a class of Halanay-type inequalities
with proportional delays. Finally, three numerical examples are given to
illustrate the effectiveness and improvement of the obtained results.