DocumentCode :
619731
Title :
A new morphological denoising algorithm to remove the noise of power signals
Author :
Zhu Youlian ; Huang Cheng
Author_Institution :
Coll. of Electron. Inf. Eng., Jiangsu Univ. of Technol., Changzhou, China
fYear :
2013
fDate :
25-27 May 2013
Firstpage :
419
Lastpage :
423
Abstract :
There exists noise in measurements of power signals. We studied structuring elements (SE) and their influence to denoising properties, and proposed a new denoising algorithm. The new algorithm uses the median morphological operation including the median opening-closing operation and the median closing-opening operation to improve denoising properties, and uses the cosine SE and the circle SE to make up the double structuring elements. In order to speed up convergence and decrease the steady state error, we take the least mean square (LMS) error as a cost function and introduce an input signal factor. Thus, we establish a variable step-size LMS (VSSLMS) adaptive algorithm. Experimental results show that the new algorithm can quickly trace changes of the system, adaptively regulate convergence step-size. It can effectively remove the noise of power signals, and has a good application prospect in signal denoising.
Keywords :
adaptive filters; adaptive signal processing; convergence; least mean squares methods; mathematical morphology; signal denoising; VSSLMS adaptive algorithm; adaptive convergence step size regulation; circle SE; cosine SE; cost function; least mean square error method; median closing opening operation; median morphological operation; median opening closing operation; morphological denoising algorithm; power signal noise removal; signal denoising; signal factor; structuring element; variable step size LMS; Convergence; Filtering; Filtering algorithms; Morphological operations; Noise; Noise reduction; Periodic structures; Adaptive Filtering; Double Structuring Elements; Morphological Filtering; Variable Step-size LMS (VSSLMS);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
Type :
conf
DOI :
10.1109/CCDC.2013.6560960
Filename :
6560960
Link To Document :
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