Uniformly Stability of Impulsive BAM Neural Networks with Delays

Existence and stability of periodic solution of impulsive BAM Type Cohen-Grossberg neural networks with delays

“…Kosko [1] introduced the bidirectional associative memories (BAMs) model, which are made up of two neural fields Fx and Fy connected in the forward direction, from Fx to Fy , and connected in the backward direction, from Fy to Fx . Since the BAM neural networks are useful in many areas, it has been researched by many scholars [2][3][4][5]. The Cohen Grossberg neural network model, initially proposed by Cohen and Grossberg [6] in 1983, have attracted considerable gzwzom@163.com: hq012@126.com attention due to its promising potential for applications III classification, parallel computing etc [7][8][9].…”

“…Recently there has been a new category of neural networks called impulsive neural networks, which display a combination of characteristics of both the continuous-time and discrete-time system [5,8,12,13,14]. Li et al [12][13][14][15] researched the periodic solution of impulsive neural networks with delays.…”

Destabilizing Effects of Impulse in Delayed Bam Neural Networks

“…Recently, several investigators have examined the global stability of impulsive DBAM networks (3) and its generalizations with much of the effort directed at obtaining global asymptotic and/or exponential stability criteria. [20][21][22][23][24][25][26][27][28][29][30] However, all the stability criteria established in Refs. 20-30 are based on the strong constraints on the impulses: the impulses do not enlarge the states of neurons, that is,…”