Matrix calculation of correlation characteristics based on spectral methods

Keywords: spectral transform, autocorrelation function, Fourier transform, Walsh transform, spectral transform at oriented basis

Abstract

The paper is devoted to the problem of calculation of autocorrelation function that is important for solving the tasks that require finding the repeating intervals of the signal or defining the main frequency of the signal against the background of non-stationary noise. The authors propose an algorithm to transform the connection between arithmetic and logical correlation functions in oriented basis into the matrix form. Comparative analysis is conducted for the computational complexity of different types of autocorrelation functions using different spectral methods - Fourier, Walsh, and oriented basis transform.

Author Biography

Liudmyla Laikova, Igor Sikorsky Kyiv Polytechnic Institute

The paper is devoted to the problem of calculation of autocorrelation function that is important for solving the tasks that require finding the repeating intervals of the signal or defining the main frequency of the signal against the background of non-stationary noise. The authors propose an algorithm to transform the connection between arithmetic and logical correlation functions in oriented basis into the matrix form. Comparative analysis is conducted for the computational complexity of different types of autocorrelation functions using different spectral methods — Fourier, Walsh, and oriented basis transform.

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Published
2020-08-27