Novel Finite-Time Reliable Control Design for Memristor-Based Inertial Neural Networks With Mixed Time-Varying Delays

The issue of finite-time stabilization (FTS) for the memristor-based inertial neural networks (MINNs) with mixed time-varying delays (MTVDs) is researched by virtue of a new analytical method in this brief. First, an appropriate reliable control strategy is proposed for MINNs, which takes the influence of actuator failures into account. Second, by combining Lyapunov functional theory with new analysis techniques, novel theoretical results to guarantee the FTS for the concerned MINNs are acquired, and the desired reliable controller gains are obtained simultaneously. In additions, compared with the previous research works, the FTS results obtained in this paper are established directly from the MINNs themselves without using variable transformation method. In the end, two simulations are exploited to show the correctness and practicability of the acquired theoretical results.

Automated summary

This brief paper researches the issue of finite-time stabilization for memristor-based inertial neural networks with mixed time-varying delays using a new analytical method. A reliable control strategy is proposed and theoretical results are obtained to guarantee the finite-time stabilization, with simulations demonstrating the correctness and practicability of the results.