A recurrent neural network with ever changing synapses
arXiv:cond-mat/0002360 · doi:10.1088/0305-4470/33/9/305
Abstract
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.
17 pages, LaTeX, 4 figures