Feature Extraction and Recognition of Analog Circuit Fault Signal Based on Wavelet Transform and Partial Singular Values Decomposition
Si-yang Liang, Jian-hong Lv
Available Online November 2012.
- https://doi.org/10.2991/citcs.2012.142How to use a DOI?
- wavelet transform; singular value decomposition; feature extraction; analog circuit
- A new algorithm for the effective characteristics' extraction of analog circuit fault signal is proposed with consideration of its complexity. The proposed method is based on wavelet transform and partial singular values decomposition. Firstly, the analog circuit fault signal is decomposed into different scales and construct the initial feature matrix with wavelet coefficients, then divide the matrix into different sub-matrix, calculate the largest singular value of each sub-matrix, and the eigenvectors are constructed by the largest singular value. Then the support vector machine (SVM) with the constructed eigenvectors as its input eigenvectors is employed to recognize the analog circuit signal of different fault mode. The results show that the characteristics of analog circuit signal are efficiently extracted and the recognition precision of SVM is also improved, the new algorithm is a feasible way to process analog circuit fault signal.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Si-yang Liang AU - Jian-hong Lv PY - 2012/11 DA - 2012/11 TI - Feature Extraction and Recognition of Analog Circuit Fault Signal Based on Wavelet Transform and Partial Singular Values Decomposition BT - 2012 National Conference on Information Technology and Computer Science PB - Atlantis Press SP - 553 EP - 556 SN - 1951-6851 UR - https://doi.org/10.2991/citcs.2012.142 DO - https://doi.org/10.2991/citcs.2012.142 ID - Liang2012/11 ER -