Information Sciences: an International Journal
Future Generation Computer Systems
Applications of multi-objective structure optimization
Neurocomputing
Hierarchical ANN system for stuttering identification
Computer Speech and Language
International Journal of Productivity Management and Assessment Technologies
Convergence of chaos injection-based batch backpropagation algorithm for feedforward neural networks
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
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The sensitivity of the global error (cost) function to the inclusion/exclusion of each synapse in the artificial neural network is estimated. Introduced are shadow arrays which keep track of the incremental changes to the synaptic weights during a single pass of back-propagating learning. The synapses are then ordered by decreasing sensitivity numbers so that the network can be efficiently pruned by discarding the last items of the sorted list. Unlike previous approaches, this simple procedure does not require a modification of the cost function, does not interfere with the learning process, and demands a negligible computational overhead