Title :
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
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;
Conference_Titel :
Embedded Computing (MECO), 2015 4th Mediterranean Conference on
Conference_Location :
Budva
Print_ISBN :
978-1-4799-8999-7
DOI :
10.1109/MECO.2015.7181892
