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—Feature selection techniques have become an apparent need for diagnostic methods such as a least squares support vector machine (LS-SVM). Most researchers use wavelet transform coefficients of the time-domain transient response data obtained from filtered analog circuits as features to train a LS-SVM classifier to diagnose faults. But wavelet coefficient(More)
—An efficient method to select an optimum set of test points for dictionary techniques in analog fault diagnosis is proposed. This is done by searching for the minimum of the entropy index based on the available test points. First, the two-dimensional integer-coded dictionary is constructed whose entries are measurements associated with faults and test(More)