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Artificial Neural Network Modelling - download pdf or read online

By Subana Shanmuganathan, Sandhya Samarasinghe

ISBN-10: 3319284932

ISBN-13: 9783319284934

ISBN-10: 3319284959

ISBN-13: 9783319284958

This booklet covers theoretical features in addition to fresh leading edge purposes of man-made Neural networks (ANNs) in typical, environmental, organic, social, commercial and automatic systems.

It offers contemporary result of ANNs in modelling small, huge and complicated platforms less than 3 different types, specifically, 1) Networks, constitution Optimisation, Robustness and Stochasticity 2) Advances in Modelling organic and Environmental Systems and three) Advances in Modelling Social and monetary Systems. The e-book goals at serving undergraduates, postgraduates and researchers in ANN computational modelling.

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Extra resources for Artificial Neural Network Modelling

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9 Weighted hidden neuron activation for the random data samples 2 and 3 and corresponding correlation matrices 26 S. Samarasinghe y (a) (b) 200 150 Neu - 2 100 -2 - 50 8 6 4 2 Neu - 3 50 -4 y Neu - 1 2 4 x Neu - 4 Neu - 5 -4 - 100 -2 -2 Neu - 1 Neu - 2 2 4 x Neu - 3 Fig. 10 Weighted hidden neuron activation of a 3-neuron a and 5-neuron b networks and corresponding correlation matrices Figure 10 illustrate convincingly that the redundant neurons can be identified by their high correlation. By removing redundant neurons, both networks are left with 2 (optimum number) of neurons.

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Haykin, Neural Networks: A comprehensive Foundation, 2nd edn. (Prentice Hall Inc, New Jersey, USA, 1999) 4. R. Reed, Pruning algorithms-A survey. IEEE Trans. Neural Networks 4, 740–747 (1993) 5. Y. S. A. Solla, Optimal brain damage, in Advances in Neural Information Processing (2), ed. S. Touretzky (1990), pp. 598–605 6. B. G. J. Wolff, Optimal brain surgeon and general network pruning. IEEE International Conference on Neural Networks, vol. 1, (San Francisco, 1992), pp. 293–298 7. B. G. Stork, Second-order derivatives for network pruning: Optimal brain surgeon, in Advances in Neural Information Processing Systems, vol.

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Artificial Neural Network Modelling by Subana Shanmuganathan, Sandhya Samarasinghe

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