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Implementing a "psychophysical" pattern classifier in a decrementing network

  • Biological Perspectives
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Artificial Neural Networks (IWANN 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 540))

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Abstract

The biological systems work starting from the sensations produced by the stimulis received from the environment. The relationship between the physical magnitude of the stimulus and the sensation produced has beeen the scope of the Psychophysics. We describe a Pattern classifier, which uses the sensations produced by the patterns and the inputs to be classified. We develope the classifying algorithm which is based on a logarithmic distance, and we show how it can be implemented in a network of simple devices. Finally, we compare the performance of this classifier versus a Gaussian classifier in a specific task.

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6. References

  • Fechner, G. T. (1860) Elements of Psychophysics Engl. transl. In G.A. Miller Mathematics and Psychology John Wiley 1964.

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  • Stevens, S.S. (1957) On the Psychophysical law Psychological Review, 64, 153–181.

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  • Stevens, S.S. (1958) Problems and Methods of Psychophysics Psychological Bulletin, 55, 177–196.

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  • Winters, J.H. and Rose, C. (1989) Minimum Distance Automata in Parallel Networks for Optimum Classification. Neural Networks, 2, 127–132.

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Alberto Prieto

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© 1991 Springer-Verlag Berlin Heidelberg

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Salinas, J.M., Dobson, V.G. (1991). Implementing a "psychophysical" pattern classifier in a decrementing network. In: Prieto, A. (eds) Artificial Neural Networks. IWANN 1991. Lecture Notes in Computer Science, vol 540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035885

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  • DOI: https://doi.org/10.1007/BFb0035885

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54537-8

  • Online ISBN: 978-3-540-38460-1

  • eBook Packages: Springer Book Archive

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