Delay-dependent stability criteria for neutral-type neural networks with interval time-varying delay signals under the effects of leakage delay

Abstract

We examine the stability problem for delayed neutral-type neural networks (NNs) with interval time-varying delay signals under the effects of leakage term by constructing a suitable Lyapunov-Krasovskii functionals (LKFs) with the triple-and four-integral terms and using the famous Jensen inequality, Wirtinger single integral inequality (WSII), and Wirtinger double integral inequality (WDII), combined with the reciprocally convex approach (RCC) for the stability of addressing NNs. Therefore, the major contribution of this study lies in a consideration of new integral inequalities and improved LKFs, fully taking the relationship between the terms in the Leibniz-Newton formula within the framework of linear matrix inequalities (LMIs). Moreover, we assume that the lower bound of interval time-varying delay is not restricted to zero. Using several examples, we show that the proposed stability criterion is less conservative than previous results. Also, the proposed technique is applied to benchmark problem that is associated with reasonable issues to showing feasibility on a real-world problem, including transporting time delay signals and leakage delay as a process variable in the quadruple-tank process system.

Robust passivity analysis of uncertain neutral-type neural networks with distributed interval time-varying delay under the effects of leakage delay

“…Samidurai et al [40] discussed the global exponential stability of neutral-type impulsive neural networks with discrete and distributed delays. In addition, Manivannan et al [30] studied on the delay-dependent stability criteria for neutral-type neural networks with interval time-varying delay signals under the effects of leakage delay and reference therein see [3,11,15,28].…”

“…Thus, the passivity theory has received a great deal of attention from the control community since 1970s [20,50]. In [7,11,15,22,28,30,37,40,41,44,55,56], the authors studied the passivity of NTNNs with time delay and obtained some passivity conditions. Hence, passivity analysis of NTNNs have been considered in recent years.…”

Stochastic Stability Criteria for Neutral Distributed Parameter Systems with Markovian Jump

“…All kinds of analysis methods have been used to discover the stochastic stability criteria of neutral-type Markovian jump systems such as Lyapunov-Krasovskii functional approach, reciprocally convex combination inequality method, and stochastic analysis theory in [13][14][15][16]. For less conservative results, the delay-dependent stability has been discussed in [17][18][19][20]. Other control methods have also been extensively and thoroughly studied such as robust delay-dependent H ∞ control [21,22], nonfragile control [23][24][25], sliding mode control [26,27], H ∞ sliding mode control [28], and the references therein.…”

Variance-constrained resilient $H_{\infty }$ state estimation for time-varying neural networks with randomly varying nonlinearities and missing measurements

“…In the past two decades, the popularization of the Internet has greatly changed our way of life through the rapid communication ways [1][2][3]. Accordingly, many scholars have witnessed successful applications of recurrent neural networks (RNNs) in wide fields including pattern recognition, image processing, associate memory and optimization domains [4][5][6]. Nevertheless, it should be noted that the nonlinearities are commonly inherent characteristics between neurons, which indeed affect the understanding and analysis of the neural networks (NNs).…”