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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Wilks, C., Eckmiller, R. (2005). Intelligent Pattern Generation for a Tactile Communication System. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_55
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DOI: https://doi.org/10.1007/11550822_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28752-0
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