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|Title:||Absolute periodicity and absolute stability of delayed neural networks||Authors:||Yi, Z.
|Issue Date:||Feb-2002||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||URI:||http://scholarbank.nus.edu.sg/handle/10635/54860||ISSN:||10577122||DOI:||10.1109/81.983875|
|Appears in Collections:||Staff Publications|
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