Please use this identifier to cite or link to this item:
|Title:||Absolute periodicity and absolute stability of delayed neural networks|
|Citation:||Yi, Z., Heng, P.A., Vadakkepat, P. (2002-02). Absolute periodicity and absolute stability of delayed neural networks. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 49 (2) : 256-261. ScholarBank@NUS Repository. https://doi.org/10.1109/81.983875|
|Abstract:||In this brief, we propose to study the absolute periodicity of delayed neural networks. A neural network is said to be absolutely periodic, if for every activation function in some suitable functional set and every input periodic vector function, a unique periodic solution of the network exists and all other solutions of the network converge exponentially to it. Absolute stability of delayed neural networks is also studied in this paper. Simple and checkable conditions for guaranteeing absolute periodicity and absolute stability are derived. Simulations for absolute periodicity are given.|
|Source Title:||IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 16, 2018
WEB OF SCIENCETM
checked on Jun 26, 2018
checked on Jul 6, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.