WSN Signal Reconstruction Based on Unknown Sparse Compressed Sensing
Pages 170 - 173
Abstract
For the signal reconstruction problem of unknown signal sparsity in compressed sensing, this paper proposes a Sparsity Adaptive Stagewise Orthogonal Matching Pursuit algorithm (SAOMP), which realizes the reconstructed signal under the condition of unknown signal sparsity. The algorithm combines the idea of adaptive thinking, variable step size iteration and piecewise orthogonal thinking. Under the condition of unknown signal sparsity, the number of supporting set atoms is adaptively selected, and finally the signal reconstruction is realized. The experimental results show that the proposed algorithm is better than the Orthogonal Matching Pursuit algorithm, the Regularized Orthogonal Matching Pursuit algorithm and the Stagewise Orthogonal Matching Pursuit algorithm for the 128-bit observation set and the 256-bit length.
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Index Terms
- WSN Signal Reconstruction Based on Unknown Sparse Compressed Sensing
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Published In
January 2020
258 pages
ISBN:9781450376907
DOI:10.1145/3378936
Copyright © 2020 ACM.
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- University of Science and Technology of China: University of Science and Technology of China
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 07 March 2020
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ICSIM '20
ICSIM '20: The 3rd International Conference on Software Engineering and Information Management
January 12 - 15, 2020
NSW, Sydney, Australia
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