Robust dissipativity analysis for delayed memristor-based inertial neural network

Global exponential convergence of delayed inertial Cohen–Grossberg neural networks

“…Shi et al [21] have investigated global exponential stabilization of inertial neural networks, and Zhang et al [29] have explored the dissipativity for delayed memristor-based inertial neural networks. However, the derivatives of time-varying delay in [21,29] are required to be no greater than one. It should be pointed out that the restricted conditions are removed in this paper.…”

Stabilization for a class of delayed switched inertial neural networks via non-reduced order method

“…Remark 1: From (3) and (4), the connection weights of SINN (1) are assumed to be depended on the state of the networks. This switching hypothesis is meaningful, for instance, weights of memristive neural networks have such properties (Guo et al, 2014; Tu et al, 2017; Xiao et al, 2019; Zhang and Wang, 2019). In fact, even if there are other types of twinkling changes of p ij † ( υ i ( t ) ) and q ij † ( υ i ( t ) ) , the main results of this article can still be extended in parallel.…”

“…Meanwhile, the author further investigated the global-generalised exponential stability for INN without variable transformation in Huang (2020). Zhang and Wang (2019) addressed the problem of robust dissipativity for memristive INN by adopting generalized Lyapunov functional method and non-reduced order strategy. Recently, the authors in Xiao et al (2020) discussed exponential stability for complex-valued INN in discrete-time domain under both reduced-order approach and non-reduced order approach.…”

Non‐fragile state estimation for second‐order memristive neural networks with unbounded time‐varying delays

“…In practice, the inertial items are also used in the circuits with inductances to simulate the membrane of hair cells in the semicircular canal in certain animals. 4 Recently, scholars have extensively studied the dynamic behavior of various INNs and obtained some interesting results on the dissipativity, [5][6][7] synchronization, [8][9][10][11][12][13] stability, [14][15][16][17][18] stabilization, 9,18 and bifurcation 19 for INNs. Significantly, the method of descending the order in the literatures above was normally used to analyze INNs.…”

“…22 Now, the dynamic analysis of various MNNs has attracted wide attention. 6,7,10,12,18,23,24 Time delays often exist in both artificial NNs and biological systems, which may result in the instability, oscillation, and low performance of the system. So the research on systems with time delay is of great significance.…”