MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641049069 A) filed by Dr R Suresh; G. Devi; and M. Meiyanathan on April 17, 2026, for Lagrange Exponential Stability Analysis Of Memristor Based Bam Neural Networks With Time Varying Delays.
Inventors include Dr R Suresh; G. Devi; and M. Meiyanathan.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: ABSTRACT This paper addresses the global exponential stability in Lagrange sense for memristor-based bidirectional associative memory neural networks (MBAMNNs) with time-varying delays. The delay-dependent Lagrange stability conditions are extracted in terms of linear matrix inequalities (LMIs) by applying a novel Lyapunov-Krasovskii functionals (LKF) and estimating the integral inequalities using Jensen-based inequality, Wirtinger inequalities. The derived conditions ensure the globally exponential stability for the proposed MBAMNNs, which means the accurate calculation of global exponential attractive set. Finally, two examples are given to show the feasibility and practicability of the proposed criteria.
Disclaimer: Curated by HT Syndication.
