ICA-wavelet Feature Extraction Method for Decoding of Pigeon Turning
[1]Dong Fangfang Shang Zhigang Liu Xinyu Wanhong.ICA-wavelet Feature Extraction Method for Decoding of Pigeon Turning[J].Journal of Zhengzhou University (Engineering Science),2017,38(03):39-43.[doi:10.13705/j.issn.1671-6833.2016.06.006]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
38
Number of periods:
2017 03
Page number:
39-43
Column:
Public date:
2017-05-28
- Title:
- ICA-wavelet Feature Extraction Method for Decoding of Pigeon Turning
- Keywords:
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local field potentials; independent component analysis; wavelet decomposition; time-frequency analysis
- CLC:
- -
- Abstract:
- In order to overcome the problems as low signal-to-noise ratio (SNR) of LFP and difficulty in identifying encoding time window when extract the features of motion intention,a method that combines independent component analysis (ICA) with Wavelet was presented to extract the features of turning.Firstly,the motion videos of animals were analyzed and the time-frequency diagrams of LFP were plotted to determine the time window of signal which encoded the motion information.Then,ICA was used to increase the SNR of LFP.Thirdly,the encode bands of LFP were extracted by wavelet method as well as the encode features were extracted by sliding time window method.Lastly,k-nearest neighbor method was used to classify the encode features.And via 1 000 times cross validation the precision was(92.35 ±5.87)％,the results showed that it could decode reliably the motion intention of animals.
- References:
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