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Paper Title: The Adaptive and Non-Adaptive Compressed Sensing Based on Average-Frame Signal to Noise Ratio (AFSNR)
Authors Name: Rayala Sateesh
Unique Id: IJRTI1707015
Published In: Volume 2 Issue 7, July-2017
Abstract: The objective of this work is to further improve the performance of the existing compressed sensing technique that uses non adaptive projection matrix. Average-Frame Signal-to-Noise Ratio (AFSNR) is calculated to evaluate the performance of the frame-based adaptive Compressed Sensing (CS) with the non-adaptive Compressed Sensing (CS) is an emerging signal acquisition technique that directly collects signals in a compressed form if they are sparse on some certain basis. It originates from the idea that it is not necessary to invest a lot of power into observing the entries of a sparse signal in all coordinates when most of them are zero anyway. Our proposed approach is adaptive projection matrix based on frame analysis which gives significantly improved speech reconstruction quality.
Keywords: compressed sensing, Adaptive Sampling, Projection Matrix, AFSNR
Cite Article: "The Adaptive and Non-Adaptive Compressed Sensing Based on Average-Frame Signal to Noise Ratio (AFSNR)", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 7, page no.85 - 89, July-2017, Available :http://www.ijrti.org/papers/IJRTI1707015.pdf
Downloads: 00079
Publication Details: Published Paper ID: IJRTI1707015
Registration ID:170427
Published In: Volume 2 Issue 7, July-2017
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ISSN Number: 2456 - 3315
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