Optimization of Modular Neural Networks with the LVQ Algorithm for Classification of Arrhythmias Using Particle Swarm Optimization

Part of the Studies in Computational Intelligence book series (SCI, volume 547)


In this chapter we describe the application of a full model of PSO as an optimization method for modular neural networks with the LVQ algorithm in order to find the optimal parameters of a modular architecture for the classification of arrhythmias. Simulation results show that this modular model optimized with PSO achieves acceptable classification rates for the MIT-BIH arrhythmia database with 15 classes.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Tijuana Institute of TechnologyTijuanaMéxico

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