Stability Analysis of Discrete Hopfield Neural Networks with Weight Function Matrix
Most matrixes of Discrete Hopfield neural networks(DHNNs) and DHNNs with delay are constant matrixes. However, most weight matrixes of DHNNses are variable in many realistic systems. So, the weight matrix and the threshold vector with time factor are considered, and DHNNs with weight function matrix (DHNNWFM) is described. Moreover, the result that if weight function matrix and threshold function vector respectively converge to a constant matrix and a constant vector that the corresponding DHNNs is stable or the weight matrix function is a symmetric function matrix, then DHNNWFM is stable, is obtained by matrix analysis.
Unable to display preview. Download preview PDF.
- 7.Zhang, Q., Wei, X., Xu, J.: On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays. Discrete Dynamics in Nature and Society. Article ID: 67675, 9p (2007)Google Scholar
- 11.Bellman, R.: Introduction to Matrix analysis. The Rand Corporation (1970)Google Scholar