22 March 1999 Data clustering via temporal segmentation of spiking neurons
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Proceedings Volume 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343070
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden
Abstract
We present a novel method for data clustering using temporal segmentation of spiking neurons. We use arrays of neurons whose pulse coupled interactions reflect the internal structure of the data set. The dynamical development of this system leads to temporal grouping of neurons that belong to the same cluster, while different clusters fire at different times. Grouping is achieved via two mechanisms: intra cluster synchrony and desynchronization between clusters. The former is induced by either instantaneous excitatory connections or delayed inhibitory ones, and the latter is induced by instantaneous inhibitory competition. We apply our method to a synthetic sum of gaussians and to the iris data set, demonstrating its capabilities.
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Irit Opher, David Horn, "Data clustering via temporal segmentation of spiking neurons", Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); doi: 10.1117/12.343070; https://doi.org/10.1117/12.343070
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