extended dissipativity synchronization for markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory

The problem of synchronization with extended dissipativity for markovian jump recurrent neural networks (mjrnns) is investigated. for mjrnns, a new memory sampled - data extended dissipative control approach is suggested here. some sufficient conditions in terms of linear matrix inequalities (lmis) are acquired by suitably establishing a relevant lyapunov - krasovskii functional (lkf), wherein the master and the slave system of mjrnns are quadratically stable. at last, a numerical section is provided, along with one of the applications in circuit theory that clearly illustrates the efficacy of the proposed method’s performance.