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Journals >
Laser & Optoelectronics Progress >
Volume 57 >
Issue 10 >
Page 101502 > Article
Laser & Optoelectronics Progress
Vol. 57, Issue 10, 101502 (2020)
Sound Event Recognition Based on Adaptive Particle Swarm Optimized Matching Tracking
Yingxin Su
*
Author Affiliations
College of Information Engineering, Eastern Liaoning University, Dandong, Liaoning 118000, China
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DOI:
10.3788/LOP57.101502
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Yingxin Su. Sound Event Recognition Based on Adaptive Particle Swarm Optimized Matching Tracking[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101502
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Fig. 1.
Animal calls and sound spectra of reconstructed signals by different algorithms. (a) Pure animal calls; (b) noise-added calls; (c) Pso-MP reconstructed signals; (d) OMP reconstructed signals; (e) APso-MP reconstructed signals
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Fig. 2.
Average recognition rate of different algorithms in four noisy environments
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Fig. 3.
ROC curve of each algorithm
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Algorithm
Ns
Nip
Time /s
MSE
NCC
SNR
OMP
218355
4459471
21705.4
0.0050
0.9241
15.9125
Pso-MP
23698
491720
1626.9
0.0255
0.7695
9.3298
APso-MP
897
3720
175.4
0.0047
0.9550
16.3921
Table 1.
Evaluation of algorithm calculation and reconstruction performance
Abstract
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Yingxin Su. Sound Event Recognition Based on Adaptive Particle Swarm Optimized Matching Tracking[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101502
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Paper Information
Category: Machine Vision
Received: Aug. 19, 2019
Accepted: Oct. 18, 2019
Published Online: May. 8, 2020
The Author Email: Su Yingxin (su_yingx_555@163.com)
DOI:
10.3788/LOP57.101502
Recommended Topics
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