Intelligent pattern generation for a tactile communication system

  • Authors:

  • C. Wilks;R. Eckmiller

  • Affiliations:

  • Division of Neural Computation, Department of Computer Science, University of Bonn, Germany;Division of Neural Computation, Department of Computer Science, University of Bonn, Germany

  • Venue:
  • ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
  • Year:
  • 2005

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Abstract

In this paper, we present an optimization method for a learning algorithm for generation of tactile stimuli which are adapted by means of the tactile perception of a human. Because of special requirements for a learning algorithm for tactile perception tuning the optimization cannot be performed basing on gradient-descent or likelihood estimating methods. Therefore, an Automatic Tactile Classification (ATC) is introduced for the optimization process. The results show that the ATC equals the tactile comparison by humans and that the learning algorithm is successfully optimized by means of the ATC.