Optimal detection of fractal signals and objects based on fractional Brownian models

Author

Parshin, Alexander ; Parshin, Yuri

Author_Institution

Radio Eng. devices Dept., Ryazan State Radio Eng. Univ., Ryazan, Russia

fYear

2015

fDate

14-18 June 2015

Firstpage

163

Lastpage

167

Abstract

Article deals with synthesis and analysis of detector of fractal signal at the background of non-correlated Gaussian noise. Model of signal is fractional Brownian motion (fBm), which describes many types of signal particularly flicker-noise. Expression for likelihood ratio is given being based on fBm models in time and spectral fields. This expression is a sufficient statistics for many problems of signal processing. Detection characteristics of fBm are calculated by analytical method and statistical simulation. Investigation results are distributed on image processing in terms of usage fractional Brownian surface (fBs) model.

Keywords

Brownian motion; Gaussian noise; flicker noise; fractals; maximum likelihood estimation; object detection; signal detection; fBm detection characteristics; flicker-noise; image processing; likelihood ratio; maximum likelihood algorithm; noncorrelated Gaussian noise; optimal fractal object detection; optimal fractal signal detection; signal processing; usage fractional Brownian surface model; Correlation; Fractals; Gaussian noise; Harmonic analysis; Probability density function; Signal to noise ratio; Surface treatment; fractional Brownian motion; maximum likelihood algorithm; signal processing; statistic methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Embedded Computing (MECO), 2015 4th Mediterranean Conference on

Conference_Location

Budva

Print_ISBN

978-1-4799-8999-7

Type

conf

DOI

10.1109/MECO.2015.7181892

Filename

7181892