New mean square exponential stability condition of stochastic fuzzy neural networks

Discrete Fractional‐Order BAM Neural Networks with Leakage Delay: Existence and Stability Results

“…There are many types of neural networks in nature: artificial networks, fuzzy networks, cellular networks, Hopfield networks and Cohen–Grossberg networks, which are all computational models inspired by biological neural networks and are used to approximate functions that are generally unknown. Undoubtedly, the way neurons semantically communicate is an area of ongoing research . Nevertheless, the bidirectional associative memory (BAM) networks are the most significant models which are composed of neurons arranged in two layers.…”

Global exponential dissipativity in mean of stochastic neural networks with infinity distributed delays

“…Many interesting results on the asymptotic behaviors of stochastic delayed neural networks [1][2][3][4][5][6][7][8] have been reported. As is well known that stability analysis of neural networks is a prerequisite for the practice design and applications.…”

“…To the best of author's knowledge, nevertheless, there are a few results about stability in mean square sense [1,3,4] and mean square asymptotic behavior of stochastic neural networks with discrete delays or infinite distributed delays [2,5,7], in the literature today. But the globally exponentially dissipate in mean generalizes the idea of a Lyapunov function * This work is supported by the Key Scientific research project of Colleges and Universities in Henan Province under Grant No.…”