Concise Exponential Stability Conditions for BAM Quaternion Memristive Neural Networks Affected by Mixed Delays

The concise exponential stability conditions for bidirectional associative memory (BAM) quaternion memristive neural networks affected by mixed delays are presented. The involved delays include multiple time-varying transmission delays and unbounded distribution delays. To show global exponential stability conditions, a new method built on the estimation of solutions is presented. The acquired stability conditions consist of several scalar inequalities, which are concise and can be easily solved. A numerical example is offered to demonstrate the applicability of the theoretical results. Notably, after a minor modification, the method built on the estimation of solutions is found to be applicable for many delayed system models.