Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/81068
Title: Recurrent neural networks: A constructive algorithm, and its properties
Authors: Tsoia, A.C.
Tan, S. 
Keywords: Convergence proof
Modified least-squares algorithm
Online learning algorithm
Radial basis function
Recurrent neural networks
Issue Date: Jun-1997
Citation: Tsoia, A.C., Tan, S. (1997-06). Recurrent neural networks: A constructive algorithm, and its properties. Neurocomputing 15 (3-4) : 309-326. ScholarBank@NUS Repository.
Abstract: In this paper, a constructive algorithm for a general recurrent neural network is proposed based on radial basis functions. It is shown that this algorithm is globally convergent. In addition, we will present two examples to illustrate the proposed method.
Source Title: Neurocomputing
URI: http://scholarbank.nus.edu.sg/handle/10635/81068
ISSN: 09252312
Appears in Collections:Staff Publications

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