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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ronggen Yang Mingwu Ren |
| Copyright Year | 2010 |
| Abstract | Wavelet transform is well know by its sparse representation of signals, with application to separate the noise from signals. Wavelet transform is appropriate to multichannel signal denoising, we consider the spatially correlation between noises and develop a new correlated noise reduction algorithm. This method is based on a change of basis that is obtained from the diagonalization of a robust estimator of the noise covariance matrix. Classical test signals were simulated to analysis the performance of the algorithm. Experiments show it outperforms the primitive wavelet transform on the one dimentional signal situations. Four channel signals are obtained from the oil pipeline leak detection project. We apply multivariate denoising to these signals and this provide denoised signals for the next step of leak recognize and time delay estimation. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 246818 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424437085 |
| DOI | 10.1109/WICOM.2010.5600238 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-09-23 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Correlation Noise reduction Noise Covariance matrix Leak detection |
| Content Type | Text |
| Resource Type | Article |
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