computer science research log in semi microbloging style


  • 07:27:51 pm on August 11, 2010 | # | 0
    Tags: , ,

    Approximation Capabilities of Neural Networks. C. Enăchescu, Journal of Numerical Analysis, Industrial and Applied Mathematics (JNAIAM), vol. 3, no. 3-4, 2008, pp. 221-230

    From the learning point of view, the approximation of a function is equivalent with the learning problem of a neural network. In this paper we want to show the capabilities of a neural network to approximate arbitrary continuous functions. We have made some experiments in order to confirm the theoretical results.


    f : X \subseteq R^{n} \to R^{m} is a continuous function

    Neural Network and Best Approximation Theory

    Given f \in F and A \subseteq F we call the distance of f from A as d(f,A)=inf\left \| f-a \right \|, a\in A


  • Modified from Prologue theme by Automattic

Leave a Comment