Exponential input-to-state stability of stochastic neural networks with mixed delays

Analysis of Exponential Stability for Neutral Stochastic Cohen-Grossberg Neural Networks with Mixed Delays

“…They are more general than time-varying delay in [1]. Also, the meansquare exponential input-to-state stability problem for a class of stochastic recurrent neural networks with mixed delays was discussed in [11,16]. But the neutral terms and Cohen-Grossberg models were not taken into account.…”

“…Meanwhile, the Cohen-Grossberg neural networks include recurrent neural networks, Hopfield neural networks, and cellular neural networks. In other words, the systems considered in [11,16] are special cases of system (1) in this paper.…”

“…The time delay may cause instability, oscillation, and divergence to stochastic neural network systems. Given the actual situation, a great number of stability results have been presented on stochastic delayed neural networks studied in the literature (see [11][12][13][14][15][16][17]). In addition, neutral-type neural network is a particular time delay system because its main feature that the derivative of system state is connected to delays.…”

Stochastic Memristive Quaternion-Valued Neural Networks with Time Delays: An Analysis on Mean Square Exponential Input-to-State Stability

“…On the other hand, it is clear that the external inputs can influence the dynamic behaviors of NNs in practical applications. As such, the ISS criterion is important to characterize the effects of external inputs [10,39,40]. Recently, several useful ISS results for stochastic RVNN and CVNN models have been published [13,[39][40][41].…”

New result on the mean-square exponential input-to-state stability of stochastic delayed recurrent neural networks

“…temperature, moisture, pressure, seasonal effects of weather, reproduction, food supplies, mating habits, etc.) plays an important role in many neural networks so that some classic neural networks models (Shu, Liu, Wang, & Qiu, 2018;Xu, Luo, Zhong, & Zhu, 2014;Zhou, Teng, & Xu, 2015) have been generalized to the non-autonomous differential equations with time-varying coefficients and delays. Unfortunately, to the best of our knowledge, few scholars have investigated the mean-square exponential input-tostate stability of SDRNNs with time-varying coefficients, so it is important to consider the its dynamical behaviours.…”