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Computing the Weights of Polynomial Cellular Neural Networks Using Quadratic Programming

  • Anna Rubi-Velez
  • Eduardo Gomez-Ramirez
  • Giovanni E. Pazienza
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

Finding the weights of a Polynomial Cellular Neural/Nonlinear Network performing a given task is not straightforward. Several approaches have been proposed so far, but they are often computationally expensive. Here, we prove that quadratic programming can solve this problem efficiently and effectively in the particular case of a totalistic network. Besides the theoretical treatment, we present several examples in which our method is employed successfully for any complexity index.

Keywords

polynomial cellular neural networks cellular automata quadratic programming 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Anna Rubi-Velez
    • 1
  • Eduardo Gomez-Ramirez
    • 2
  • Giovanni E. Pazienza
    • 3
  1. 1.Enginyeria i Arquitectura La SalleUniversitat Ramon LlullBarcelonaSpain
  2. 2.LIDETEA, Posgrado e InvestigacionUniversidad La SalleMexico CityMexico
  3. 3.Cellular Sensory and Wave Computing LaboratoryMTA-SZTAKIBudapestHungary

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