Abstract:
It is known that symmetric cellular neural networks (CNNs) are completely stable. It is shown that CNNs with delay (DCNNs), though symmetric, can become unstable if the d...Show MoreMetadata
Abstract:
It is known that symmetric cellular neural networks (CNNs) are completely stable. It is shown that CNNs with delay (DCNNs), though symmetric, can become unstable if the delay is suitably chosen: actually such networks can exhibit periodic cycles. Moreover, a sufficient condition is presented to ensure complete stability: such a condition establishes a relation between the delay time and the parameters of the network.<>
Published in: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications ( Volume: 40, Issue: 3, March 1993)
DOI: 10.1109/81.222796
