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Probabilistic neural-network structure determination for pattern classification

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3 Author(s)
K. Z. Mao ; Centre for Signal Process., Nanyang Technol. Univ., Singapore ; K. -C. Tan ; W. Ser

Network structure determination is an important issue in pattern classification based on a probabilistic neural network. In this study, a supervised network structure determination algorithm is proposed. The proposed algorithm consists of two parts and runs in an iterative way. The first part identifies an appropriate smoothing parameter using a genetic algorithm, while the second part determines suitable pattern layer neurons using a forward regression orthogonal algorithm. The proposed algorithm is capable of offering a fairly small network structure with satisfactory classification accuracy

Published in:

IEEE Transactions on Neural Networks  (Volume:11 ,  Issue: 4 )