WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-21
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
For wireless network microseismic monitoring and the problems of low compression ratio and high energy consumption of communication, this paper proposes a segmentation compression algorithm according to the characteristics of the microseismic signals and the compression perception theory (CS) used in the transmission process.
The algorithm will be collected as a number of nonzero elements of data segmented basis, by reducing the number of combinations of nonzero elements within the segment to improve the accuracy of signal reconstruction, while taking advantage of the characteristics of compressive sensing theory to achieve a high compression ratio of the signal.
Experimental results show that, in the quantum chaos immune clone refactoring (Q-CSDR) algorithm for reconstruction algorithm, under the condition of signal sparse degree higher than 40, to be more than 0.4 of the compression ratio to compress the signal, the mean square error is less than 0.01, prolonging the network life by 2 times.
American Psychological Association (APA)
Liu, Zhouzhou& Wang, Fubao. 2015. WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073165
Modern Language Association (MLA)
Liu, Zhouzhou& Wang, Fubao. WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1073165
American Medical Association (AMA)
Liu, Zhouzhou& Wang, Fubao. WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073165
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073165