Efficient BP Algorithms for General Feedforward Neural Networks

Authors:
S. España-Boquera;F. Zamora-Martínez;M. J. Castro-Bleda;J. Gorbe-Moya
Affiliations:
DSIC, Universidad Politécnica de Valencia, Valencia, Spain;LSI, Universitat Jaume I, Castellón, Spain;DSIC, Universidad Politécnica de Valencia, Valencia, Spain;DSIC, Universidad Politécnica de Valencia, Valencia, Spain
Venue:
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Year:
2007

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Abstract

The goal of this work is to present an efficient implementation of the Backpropagation (BP) algorithm to train Artificial Neural Networks with general feedforward topology. This will lead us to the "consecutive retrieval problem" that studies how to arrange efficiently sets into a sequence so that every set appears contiguously in the sequence. The BP implementation is analyzed, comparing efficiency results with another similar tool. Together with the BP implementation, the data description and manipulation features of our toolkit facilitates the development of experiments in numerous fields.