ABSTRACT
In underdetermined blind source separation (BSS) algorithms, source number estimation is a precondition and a difficulty. An improved source number estimation method based on wavelet analysis and singular value decomposition is pro-posed. First, the whitened observed signals are decomposed by wavelet analysis method. Next, the decomposed wavelet coefficients are reconstructed separately. Low frequency wavelet coefficients, the highest frequency wavelet coefficients, and original observed signals are chosen to form a new observed signals matrix. Then, covariance matrix of this new signal matrix is calculated, and eigenvalues of covariance matrix are calculated. Based on the obtained eigenvalues, a new calculation formula of judging threshold for source signals and noise is proposed. The proposed algorithm is validated by simulation.
- Kritchman, S. and Nadler, B. 2008. Determining the number of components in a factor model from limited noisy data. Chemometrics and Intelligent Laboratory Systems 94 (June 2008), 19--32.Google Scholar
- Murty, S. 1994. A technique to determine the number of incoherent sources to the response of a system. Mechanical System and Signal Processing 8, 4, 363--380.Google ScholarCross Ref
- Bofill, P., Zibulevsky M. 2001. Underdetermined blind source separation using sparse representations. Signal Processing 81(June 2001), 2353--2362.Google Scholar
- Mahmuddin, M. and Yusof, Y. 2010. Automatic estimation total number of cluster using a hybrid test-and-generate and K-means algorithm. International Conference on Computer Applications and Industrial Electronics (ICCAIE), 593--596.Google Scholar
- Tan, B. H., Zhao, M., and Xie, S. L. 2009. Sources number estimation and blind separation algorithm based on unsupervised learning. Systems Engineering and Electronics 31, 8 (Aug. 2009), 1790--1794.Google Scholar
- Jalil, T. and Nasser, M. 2012. A variational Bayes approach to the underdetermined blind source separation with automatic determination of the number of sources. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 253--256.Google Scholar
- Zhao, X. Z. and Ye, B. Y. 2016. Singular value decomposition packet and its application to extraction of weak fault feature. Mechanical Systems and Signal Processing 70-71 (Sept. 2016), 73--86.Google Scholar
- Zuo, C. H., Zhang, J., and Chen, C. J. 2015. A Blind estimation method of source number in underdetermined mixing cases. Electronic Measurement Technology 38, 6 (June 2016), 113--117.Google Scholar
Index Terms
- A Modified Source Number Estimation Method based on Wavelet Analysis and Singular Value Decomposition
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