tailieunhanh - Báo cáo hóa học: "Integro-differential inequality and stability of BAM FCNNs with time delays in the leakage terms and distributed delays"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Integro-differential inequality and stability of BAM FCNNs with time delays in the leakage terms and distributed delays | Zhang and Li Journal of Inequalities and Applications 2011 2011 43 http content 2011 1 43 Journal of Inequalities and Applications a SpringerOpen Journal RESEARCH Open Access Integro-differential inequality and stability of BAM FCNNs with time delays in the leakage terms and distributed delays Xinhua Zhang and Kelin Li Correspondence lkl@ School of Science Sichuan University of Science Engineering Sichuan 643000 PR China Springer Abstract In this paper a class of impulsive bidirectional associative memory BAM fuzzy cellular neural networks FCNNs with time delays in the leakage terms and distributed delays is formulated and investigated. By establishing an integro-differential inequality with impulsive initial conditions and employing M-matrix theory some sufficient conditions ensuring the existence uniqueness and global exponential stability of equilibrium point for impulsive BAM FCNNs with time delays in the leakage terms and distributed delays are obtained. In particular the estimate of the exponential convergence rate is also provided which depends on the delay kernel functions and system parameters. It is believed that these results are significant and useful for the design and applications of BAM FCNNs. An example is given to show the effectiveness of the results obtained here. Keywords bidirectional associative memory fuzzy cellular neural networks impulses distributed delays global exponential stability 1 Introduction The bidirectional associative memory BAM neural network models were first introduced by Kosko 1 . It is a special class of recurrent neural networks that can store bipolar vector pairs. The BAM neural network is composed of neurons arranged in two layers the X-layer and Y-layer. The neurons in one layer are fully interconnected to the neurons in the other layer. Through iterations of forward and backward information flows between the two layer it performs a two-way associative search for .