A recurrent neural network with ever changing synapses

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

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17 pages, LaTeX, 4 figures

Scientific paper

10.1088/0305-4470/33/9/305

A recurrent neural network with noisy input is studied analytically, on the basis of a Discrete Time Master Equation. The latter is derived from a biologically realizable learning rule for the weights of the connections. In a numerical study it is found that the fixed points of the dynamics of the net are time dependent, implying that the representation in the brain of a fixed piece of information (e.g., a word to be recognized) is not fixed in time.

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