Data-Dependent Weight Initialization in the Hopfield Neural Network Classifier: Application to Natural Colour Images

Author:

Sammouda R.1

Affiliation:

1. Department of Computer Science, University of Sharjah, Sharjah, P.O. Box 27272, UAE;

Publisher

Informa UK Limited

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Hardware and Architecture,Software

Reference10 articles.

1. C.M. Bishop,neural networks for pattern recognition, Chapter 7 (Oxford University Press, 1995), 253–294.

2. F.V.D. Berg, particle swarm weight initialization in multi-layer perceptron artificial neural networks,IEEE Swarm Intelligence Symposium Proceeding, 2003, 182–186.

3. S. Devidhruba, C. Pandashyam, & S. Pattnaik, initializing artificial neural networks by genetic algorithm to calculate the resonant frequency of single shorting post rectangular patch antenna,IEEE Antennas and Propagation Society International Symposium, 3, 2003, 144–147.

4. L.N. de Castro, E.M. Iyoda, F.J.V. Zuben, & R. Gudwin, Feedforward neural network initialization: An evolutionary approach,7th Brazilian Symposium on Neural Networks Proceeding, 1998, 43–48.

5. R. Sammouda, N. Niki, & H. Nishitani, A comparison of hopfield neural network and boltzmann machine in segmenting MR images ofthe brain,IEEE Transactions onNuclear Science, 43(6), 1996, 349–356.

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