This paper explored the topic of extended dissipativity analysis for Markovian jump neural networks (MJNNs) that were influenced by time-varying delays.A distinctive Lyapunov functional, distinguished THERMAL PROTECTANT SPRAY by a non-zero delay-product types, was presented.This was achieved by combining a Wirtinger-based double integral inequality with a flexible matrix set.This novel methodology addressed the limitations of the slack matrices found in earlier research.
As a result, a fresh 1211 condition for extended dissipativity in MJNNs was formulated, utilizing an exponential type reciprocally convex inequality in conjunction with the newly introduced nonzero delay-product types.A numerical example was included to demonstrate the effectiveness of the proposed methodology.