Artificial Metaplasticity: Application to MIT-BIH Arrhythmias Database

  • Santiago Torres-Alegre
  • Juan Fombellida
  • Juan Antonio Piñuela-Izquierdo
  • Diego Andina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9107)

Abstract

Artificial Metaplasticity are Artificial Learning Algorithms based on modelling higher level properties of biological plasticity: the plasticity of plasticity itself, so called Biological Metaplasticity. Artificial Metaplasticity aims to obtain general improvements in Machine Learning based on the experts generally accepted hypothesis that the Metaplasticity of neurons in Biological Brains is of high relevance in Biological Learning. Artificial Metaplasticity Multilayer Perceptron (AMMLP) is the application of Metaplasticity in MLPs ANNs trying to improve uniform plasticity of the Backpropagation algorithm. In this paper two different AMMLP algorithms are applied to the MIT-BIH electro cardiograms database and results are compared in terms of network performance and error evolution.

Keywords

Metaplasticity Plasticity MLP MMLP AMP MIT-BIH ECGs Feature Extraction Machine Learning Artificial Neural Network 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Santiago Torres-Alegre
    • 1
  • Juan Fombellida
    • 1
  • Juan Antonio Piñuela-Izquierdo
    • 2
  • Diego Andina
    • 1
  1. 1.Group for Automation in Signals and CommunicationsTechnical University of MadridMadridSpain
  2. 2.Universidad Europea de MadridMadridSpain

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