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Self-organizing network for optimum supervised learning

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2 Author(s)
Tenorio, M.F. ; Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA ; Lee, W.-T.

A new algorithm called the self-organizing neural network (SONN) is introduced. Its use is demonstrated in a system identification task. The algorithm constructs a network, chooses the node functions, and adjusts the weights. It is compared to the backpropagation algorithm in the identification of the chaotic time series. The results show that SONN constructs a simpler, more accurate model, requiring less training data and fewer epochs. The algorithm can also be applied as a classifier

Published in:

Neural Networks, IEEE Transactions on  (Volume:1 ,  Issue: 1 )

Date of Publication:

Mar 1990

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