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View all- Li YChen W(2023)A Correlation Coefficient Sparsity Adaptive Matching Pursuit AlgorithmIEEE Signal Processing Letters10.1109/LSP.2023.325246930(190-194)Online publication date: 2023
Weak Sparsity Adaptive Matching Pursuit Algorithm based on Environmental Monitoring Sensor Network Data
Pages 160 - 164
Abstract
Due to the undetermined signal sparsity in environmental monitoring applications, the compressed sensing reconstruction algorithm with sparsity adaptive characteristics has better application value. In order to improve the reconstruction accuracy of the reconstruction algorithm, this paper proposes a weak sparsity adaptive matching pursuit algorithm. Firstly, the algorithm constructs the candidate set by weak selection, and then introduces the backtracking idea to filter the candidate set atoms and form a support set. In addition, the algorithm applies the idea of variable step size, and selects different step sizes for different iterations to achieve more accurate and complete reconstruction. Simulation experiments show that the improved algorithm proposed in this paper has higher reconstruction accuracy than similar algorithms.
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January 2020
258 pages
ISBN:9781450376907
DOI:10.1145/3378936
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Published: 07 March 2020
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ICSIM '20: The 3rd International Conference on Software Engineering and Information Management
January 12 - 15, 2020
NSW, Sydney, Australia
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View all- Li YChen W(2023)A Correlation Coefficient Sparsity Adaptive Matching Pursuit AlgorithmIEEE Signal Processing Letters10.1109/LSP.2023.325246930(190-194)Online publication date: 2023
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