A Variational Approach to Associative Memory
نویسنده
چکیده
The purpose of this paper is to show how fundamental results from variational approximation theory can be exploited to design recurrent associative memory networks. We begin by stating the problem of learning a set of given patterns to an associative memory network as a hypersurface construction problem, then we show that the associated approximation problem is well posed. Characterizing and determining such a solution will lead us to introduce the desired associative memory network which can be viewed as a recurrent radial basis function (RBF) network which has as many attractor states as there are fundamental patterns (no spurious memories). Subject classiication: AMS(MOS) 65F10, 65B05.
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