A formal selection and pruning algorithm for feedforward artificial neural network optimization.

A formal selection and pruning algorithm for feedforward artificial neural network optimization. Research Abstract Details 

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A formal selection and pruning algorithm for feedforward artificial neural network optimization. Abstract Text:

P S Ponnapalli,K C Ho,M Thomson,

A formal selection and pruning technique based on the concept of local relative sensitivity index is proposed for feedforward neural networks. The mechanism of backpropagation training algorithm is revisited and the theoretical foundation of the improved selection and pruning technique is presented. This technique is based on parallel pruning of weights which are relatively redundant in a subgroup of a feedforward neural network. Comparative studies with a similar technique proposed in the literature show that the improved technique provides better pruning results in terms of reduction of model residues, improvement of generalization capability and reduction of network complexity. The effectiveness of the improved technique is demonstrated in developing neural network models of a number of nonlinear systems including three bit parity problem, Van der Pol equation, a chemical processes and two nonlinear discrete-time systems using the backpropagation training algorithm with adaptive learning rate.

A formal selection and pruning algorithm for feedforward artificial neural network optimization. Publishing Authors By Initials

PS Ponnapalli,KC Ho,M Thomson,

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A formal selection and pruning algorithm for feedforward artificial neural network optimization. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: IEEE transactions on neural networks / a publicati

VOLUME: 10

Page Numbers: 964-8

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ISSN: 1045-9227

DAY: 6

MONTH: 02

YEAR: 1999

A formal selection and pruning algorithm for feedforward artificial neural network optimization. Information

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LANGUAGE: eng

NlmUniqueID: 101211035

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Grant and Affiliation Information for A formal selection and pruning algorithm for feedforward artificial neural network optimization.

AFFILIATION: Dept. of Electr. and Electron. Eng., Manchester Metropolitan Univ.

Country: United States

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MEDLINETA: IEEE Trans Neural Netw

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