Universal Approximation and the Topological Neural Network
Michael A. Kouritzin,
Daniel Richard
Abstract:A topological neural network (TNN), which takes input data from a Tychonoff topological space instead of the usual finite dimensional space, is introduced. As a consequence, a distributional neural network (DNN) that takes Borel measures as data is also introduced. Combined these new neural networks facilitate things like recognizing long range dependence, heavy tails and other properties in stochastic process paths or like acting on belief states produced by particle filtering or hidden Markov model algorithm… Show more
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