
	Information Technology Journal
	Year: 2008 \| Volume: 7 \| Issue: 2 \| Page No.: 320-325 DOI: 10.3923/itj.2008.320.325

Multi-Resolution Signal Decomposition and Approximation Based on SVMS

Wang Liejun, Jia Zhenhong and Lu Zhaogan

Abstract: Support Vector Machines (SVMs) and Multi-Resolution Analysis (MRA) both have been developed for solving signal approximation problem. Replacing the approximation criterion of MRA by which be used in SVMs, multi-resolution signal decomposition and approximation algorithm based on SVMs can be derived. The advantage of this algorithm not only reduces the approximation error by introducing structure risk, but also has better smoothness of approximation function. Experiment illustrates that this algorithm has better approximation performance than conventional MRA when applying it to the approximation of stationary signal.

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How to cite this article:

Wang Liejun, Jia Zhenhong and Lu Zhaogan, 2008. Multi-Resolution Signal Decomposition and Approximation Based on SVMS. Information Technology Journal, 7: 320-325.

DOI: 10.3923/itj.2008.320.325

URL: https://scialert.net/abstract/?doi=itj.2008.320.325

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