Associative memory and segmentation in the network composed of spiking neurons
  Revised:March 25, 2004
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DOI:10.7511/jslx20062035
KeyWord:Hodgkin-Huxley
PENG Jian-hua  L(U) Xiao-li  LIU Yan-zhu
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Abstract:
      We present in this paper some results on the temporal segmentation and retrieval of stored memories or patterns using neural networks composed of the widely used model neurons in the neuroscience society,the Hodgkin-Huxley neurons.For an input pattern which is an overlapped superposition of several stored patterns,it is shown that the proposed neuronal network model is capable of segmenting out each pattern one after another in the time domain as synchronous firings of a subgroup of neurons.If a corrupted input pattern is presented,the network is shown to be able to retrieve the perfect one,that is it has the function of associative memory.