DocumentCode :
676307
Title :
Signal segmentation based on direct use of statistical moments and Renyi entropy
Author :
Aiordachioaie, Dorel
Author_Institution :
Dunarea de Jos Univ. of Galati, Galati, Romania
fYear :
2013
fDate :
7-9 Nov. 2013
Firstpage :
359
Lastpage :
362
Abstract :
Signal segmentation based on statistical moments is considered in this paper. This method is called direct method, in opposition with methods based on transformation of the signal, which are referred as being indirect methods. The objective of the paper is to evaluate the potential of statistical moments for signal segmentation and to obtain a reference for other methods. The paper uses heuristic algorithms for the change detection and suggests a performance criterion based on the detection and false alarm probabilities. Results are satisfactory but could be used as references in the evaluations of other more complex methods, e.g. those based on the time-frequency transforms. All manuscripts must be in English, printed in black ink.
Keywords :
entropy; heuristic programming; signal synthesis; statistical analysis; time-frequency analysis; English; Renyi entropy; black ink; change detection; false alarm probabilities; heuristic algorithms; performance criterion; signal segmentation; statistical moments; time frequency transforms; Decision support systems; Three-dimensional displays; Statistical signal processing; change detection; estimation; segmentation; signal detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Computer and Computation (ICECCO), 2013 International Conference on
Conference_Location :
Ankara
Type :
conf
DOI :
10.1109/ICECCO.2013.6718302
Filename :
6718302
Link To Document :
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