SVIBOR - Project code: 2-07-401

MINISTRY OF SCIENCE AND TECHNOLOGY

Strossmayerov trg 4, HR - 10000 ZAGREB
tel.: +385 1 459 44 44, fax: +385 1 459 44 69
E-mail: ured@znanost.hr

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Project code: 2-07-401


RESEARCH IN DETECTION THEORY OF THE STOCHASTIC SIGNAL IN NOISE


Main researcher: UGRINOVIĆ, KOSTA (112456)



Assistants
Type of research: applied
Duration from: 06/01/92. to 05/31/95.

Papers on project (total): 6
Papers on project quoted in Current Contents: 1
Institution name: Fakultet prirodoslovno matematičkih znanosti i odgojnih područja, Split (177)
Department/Institute: Department of mathematics and informatics
Address: Nikole Tesle 12
City: 21000 - Split, Croatia
Communication
Phone: 385 (0)21 587133
Fax: 385 (0)21 362431
E-mail: ugrin@mapmf.pmfst.hr
Phone: 385 (0)21 587009

Summary: Detection of the sophisticated stochastic signal in noise is considered. The signal is supposed to be the sum of two kinds of components: wideband and narrowband ones. Due to this assumption it was defined the mathematical model of the signal power spectral density. So defined the model became the basis of the new synthesis method regarding to the sophisticated signal detection optimum structure. In order to synthesize the optimum structure both the likelihood ratio statistical test and the Neyman-Pearson criterion are used. To evaluate the optimum structure performance the ROC (Receiver Operating Characteristics) diagram are investigated and compared with the suboptimum structures ROC diagrams.

Keywords: detection theory, stochastic signal, statistical test, likelihood ratio

Research goals: Taking into consideration all in detection theory about stochastic signals in noise it was intended to derive a general algorithm for the detection of sophisticated stochastic signal in noise. The stochasic signal was defined as a sum of two or more statistical independent parts, and it was supposed to be ergodic Gaussian process of long time duration. For this assumption the discrete signal samples in the frequency domain are statistical independent, and on this basis the optimum detection algorithm was researched. In the research work the likelihood ratio statistical test and the Neyman-Pearson criterion were used. The research result go to show that the indirect measure of the detection probability depends on the number of discrete frequency samples and on the power spectral densities input ratio of additive stochastic signal components and noise.

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Last update: 10/01/95
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