원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol.9 No.5
2016.05
pp.347-356
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
A novel design of dual-tree complex wavelet transform (DTCWT) and fastICA was proposed, aiming at the noise interference and aliasing between multi-channels sEMG signals. Firstly, DTCWT was utilized to decompose signals to different frequency band. Secondly, an improved LMS adaptive filter was designed for filtering sub band noise layer by layer. Finally, fastICA algorithm was introduced to separate crosstalk between channels. Some experiments were carried out to compare the proposed method with other algorithms, and the results showed that the algorithm proposed could filter noise effectively, keep better convergence especially in low signal-to-noise ratio and eliminate crosstalk more thoroughly by fastICA.
목차
Abstract
1. Introduction
2. Background Matherials
2.1.s MVSS Algorithm
2.2. Dual Tree Complex Wavelet Transform
2.3. FastICA algorithm
3. DTCWT-SMVSS Algorithm for sEMG Filtering
3.1. Algorithm Structure
3.2. Signals Decomposition and Reconstruction
3.3. SMVSS Agorithm
4. Experimental Analysis
4.1. The Results of DTCWT-SMVSS Filtering
4.2. Actually Signal Experiments
4.3. FastICA Experiment Results
5. Conclusion
References
1. Introduction
2. Background Matherials
2.1.s MVSS Algorithm
2.2. Dual Tree Complex Wavelet Transform
2.3. FastICA algorithm
3. DTCWT-SMVSS Algorithm for sEMG Filtering
3.1. Algorithm Structure
3.2. Signals Decomposition and Reconstruction
3.3. SMVSS Agorithm
4. Experimental Analysis
4.1. The Results of DTCWT-SMVSS Filtering
4.2. Actually Signal Experiments
4.3. FastICA Experiment Results
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보