Best neural simultaneous approximation
Authors/Creators
- 1. Department of Mathematics, College of Education for Pure Sciences, University of Babylon, Iraq
Description
For many years, approximation concepts has been investigated in view of neural networks for the several applications of the two topics. Researchers studied simultaneous approximation in the 2-normed space and proved essential theorems concern with existence, uniqueness and degree of best approximation. Here, we define a new 2-norm in πΏπ-space, with π < 1, so we call it πΏπ quasi 2- normed space (πΏπ,2 ). The set of approximations is a space of feedforward neural networks that is constructed in this paper. Existence and uniqueness of best neural approximation for a function from πΏπ,2 is proved, describing the rate of best approximation in terms of modulus of smoothness.
Files
53 21517 2jun20 (lia).pdf
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(351.7 kB)
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