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

  • Jonathan Amezcua
  • Patricia Melin
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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