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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. Keywords-wavelet transform; singular value decomposition; feature extraction; analog circuit

Feature Extraction and Recognition of Analog Circuit Fault Signal Based on Wavelet Transform and Partial Singular Values Decomposition