On the Problem of Choosing Optimal Methods for Approximating Functions

Author:

Bordanov I A,Zhiganov S N,Danilin S N

Abstract

Abstract The materials of the article relate to the field of optimization of control systems and signal processing when preparing models for technical implementation. The informational level of structural and functional decomposition of models of approximators of square root functions is considered. The article investigates two classes of computational methods: sequential - polynomials of the best approximation and parallel - multilayer feedforward neural networks. For each of the classes, using particular examples, the approximation error was calculated according to the criteria of the maximum absolute error and the area of the error function, as well as the computational costs as the sum of the number of mathematical operations and queries in the memory of the calculator.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference19 articles.

1. A survey of neuromorphic computing and neural networks in hardware;Schuman,2017

2. A Numerical simulation of neural network components of controlling and measuring systems;Danilin,2014

3. Neural network control over operation accuracy of memristor-based hardware;Danilin,2015

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