Abstract: Sparse decomposition represents a signal as a linear combination of a small number of atoms in a redundant dictionary. The accuracy of its decomposition has an important influence on its wide application.A sparse decomposition method based on quantum evolution algorithm is proposed. The Gabor atoms are encoded by the enhanced qubit probability amplitude. The simplified form of gradient evolution operation and generation by generation reduction mutation operation are used to update the individual population. And the inner products of the residual signal of sparse decomposition and Gabor atoms are used as the fitness to filter out the best atoms for each sparse decomposition. Two experiments of sparse decomposition of simulation signals and the fault feature extraction experiments of the bearing vibration signals are carried out. The results are proved that the proposed method has a higher resolution than the other methods.

Key words: quantum optics, quantum evolutionary algorithm, generation by generation reduction mutation operation, signal sparse decomposition