Extended dissipative output-feedback control for discrete-time bidirectional associative memory neural networks via delay-partitioning approach

This paper is concerned with the analysis of an extended dissipativity performance for a class of bidirectional associative memory (BAM) neural networks (NNs) having time-varying delays. To achieve this, the idea of the delay-partitioning approach is used, where the range of time-varying delay factors is partitioned into a finite number of equidistant subintervals. A delay-partitioning based Lyapunov–Krasovskii function is introduced on these intervals, and some new delay-dependent extended dissipativity results are established in terms of linear matrix inequalities, which also depend on the partition size of the delay factor. Further, numerical examples are performed to acknowledge the extended dissipativity performance of delayed discrete-time BAM NN; further, four case studies were explored with their simulations to validate the impact of the delay-partitioning approach.