Abstract
Tree based Orthogonal matching pursuit is proposed to overcome the convergence of sparse decomposition. Sparse decomposition can be fast solved by tree based matching pursuit, however, the tree based pursuit is locally best in essence, so it convergences very slowly. We propose the orthogonal matching pursuit algorithm that maintains full backward orthogonality of the residual (error) at every step and thereby leads to improved convergence. Also, it guarantees the sparsity of results and exactly of reconstructed image. Speech signal and earthquake signal are tested via Tree based orthogonal matching pursuit separately, both of which have better convergence performance than tree based matching pursuit.
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Zhao, S., Zhang, Q., Yang, H. (2011). Orthogonal Matching Pursuit Based on Tree-Structure Redundant Dictionary. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23324-1_50
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DOI: https://doi.org/10.1007/978-3-642-23324-1_50
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