![](/images/graphics-bg.png)
WSNs Compressed Sensing Signal Reconstruction Based on Improved Kernel Fuzzy Clustering and Discrete Differential Evolution Algorithm
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-06-16
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
To reconstruct compressed sensing (CS) signal fast and accurately, this paper proposes an improved discrete differential evolution (IDDE) algorithm based on fuzzy clustering for CS reconstruction.
Aiming to overcome the shortcomings of traditional CS reconstruction algorithm, such as heavy dependence on sparsity and low precision of reconstruction, a discrete differential evolution (DDE) algorithm based on improved kernel fuzzy clustering is designed.
In this algorithm, fuzzy clustering algorithm is used to analyze the evolutionary population, which improves the pertinence and scientificity of population learning evolution while realizing effective clustering.
The differential evolutionary particle coding method and evolutionary mechanism are redefined.
And the improved fuzzy clustering discrete differential evolution algorithm is applied to CS reconstruction algorithm, in which signal with unknown sparsity is considered as particle coding.
Then the wireless sensor networks (WSNs) sparse signal is accurately reconstructed through the iterative evolution of population.
Finally, simulations are carried out in the WSNs data acquisition environment.
Results show that compared with traditional reconstruction algorithms such as StOMP, the reconstruction accuracy of the algorithm proposed in this paper is improved by 36.4-51.9%, and the reconstruction time is reduced by 15.1-31.3%.
American Psychological Association (APA)
Liu, Zhouzhou& Li, Shi-ning. 2019. WSNs Compressed Sensing Signal Reconstruction Based on Improved Kernel Fuzzy Clustering and Discrete Differential Evolution Algorithm. Journal of Sensors،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1191472
Modern Language Association (MLA)
Liu, Zhouzhou& Li, Shi-ning. WSNs Compressed Sensing Signal Reconstruction Based on Improved Kernel Fuzzy Clustering and Discrete Differential Evolution Algorithm. Journal of Sensors No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1191472
American Medical Association (AMA)
Liu, Zhouzhou& Li, Shi-ning. WSNs Compressed Sensing Signal Reconstruction Based on Improved Kernel Fuzzy Clustering and Discrete Differential Evolution Algorithm. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1191472
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191472