Abstract
Information in the nervous system has often been considered as being represented by simultaneous discharges of a large set of neurons. We propose a learning mechanism for neural information processing in a simulated cortex model. Also, a new paradigm for pattern recognition by oscillatory neural networks is proposed. The relaxation time of the oscillatory networks is used as a criterion for novelty detection.
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© 1997 Springer-Verlag Berlin Heidelberg
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Ho, T.V., Rouat, J. (1997). A novelty detector using a network of integrate and fire neurons. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020140
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DOI: https://doi.org/10.1007/BFb0020140
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