A compression-based backward approach for the forward sparse modeling with application to speech coding. (August 2017)

• Record Type: Journal Article
• Authors: Omara, A.N.; Hefnawy, A.A.; Zekry, Abdelhalim
• Is Part Of: Computers & electrical engineering. Volume 62(2017)
• Page Start: 612
• Page End: 629
• Publication Date: 2017-08
• Subjects: Sparse representation -- Forward greedy pursuit -- Backward elimination -- Backward replacement -- Speech coding; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.05.005
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: This paper concentrates on the development of an efficient and robust backward solution for the forward sparse greedy algorithms and applies this solution in the field of speech compression. All existing backward solutions are based on constraining more and more weights to zero while re-optimizing the remaining nonzero weights to compensate. Our approach is termed Backward Replacement (BRe) algorithm and its idea is to replace the k − sparse weights vector with a k − sparse symmetric matrix. The key result of this paper showed that, the replacement approach has demonstrated successfully the superiority over existing backward elimination algorithms in both enhancing the compression capabilities of the forward greedy algorithms, and reducing the time complexity.