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
Dipartimento di Electtronica, Politecnico di Torino, Torino, Italy
Dipartimento di Electtronica, Politecnico di Torino, Torino, Italy
Dipartimento Di Matematica, Politecnico di Torino, Torino, Italy
Dipartimento di Electtronica, Politecnico di Torino, Torino, Italy
Dipartimento di Electtronica, Politecnico di Torino, Torino, Italy
Dipartimento Di Matematica, Politecnico di Torino, Torino, Italy