Properties of the Hermite Activation Functions in a Neural Approximation Scheme

  • Bartlomiej Beliczynski
Conference paper

DOI: 10.1007/978-3-540-71629-7_6

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4432)
Cite this paper as:
Beliczynski B. (2007) Properties of the Hermite Activation Functions in a Neural Approximation Scheme. In: Beliczynski B., Dzielinski A., Iwanowski M., Ribeiro B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg

Abstract

The main advantage to use Hermite functions as activation functions is that they offer a chance to control high frequency components in the approximation scheme. We prove that each subsequent Hermite function extends frequency bandwidth of the approximator within limited range of well concentrated energy. By introducing a scalling parameter we may control that bandwidth.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Bartlomiej Beliczynski
    • 1
  1. 1.Warsaw University of Technology, Koszykowa 75, 00-662 WarsawPoland

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