K-SVD: Dictionary Developing Algorithms for Sparse Representation of Signal.
Snehal G.Patil1, A. G. Patil2
1Ms:Snehal Patil Electronics and Telecommunication, BATU University, PVPIT, Budhgaon, Sangli, India.
2Prof:A.G.Patil, Electronics and Telecommunication, BATU University, PVPIT, Budhgaon, Sangli, India.
Manuscript received on 1 August 2019. | Revised Manuscript received on 6 August 2019. | Manuscript published on 30 September 2019. | PP: 284-287 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4139098319/19©BEIESP | DOI: 10.35940/ijrte.C4139.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The sparse representation of signal is more interested in recent days. It contains overcomplete dictionaries that provides the signal atom. All signals of sparse explained with the help of linear combination of atom. Our proposed system mainly worked on different types of pursuit algorithm that decompose signal with respect to given dictionary D. In K-SVD algorithm description with the help of K-means algorithm. In analytical manner we developed all the algorithm with the help of calculation of dictionary D and it also apply to various method to get updated data. After correction of data we developed K-SVD algorithm which is adaptable. It also work in future work.
Keywords: Basis Pursuit, Dictionary, FOCUSS, K-means, K-SVD, Matching Pursuit.
Scope of the Article: Web Algorithms.