New sufficient conditions for absolute stability of neural networks
Xue-Bin Liang, Lide Wu · IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications · 1998
The main result obtained in this paper is that for a neural network with interconnection matrix T, if -T is quasi-diagonally row-sum or column-sum dominant, then the network system is absolutely stable. The above two sufficient conditions for absolute stability are independent of the existing sufficient ones in the literature. Under either of the above two sufficient conditions for absolute stability, the vector field defined by the network system is also structurally stable.