Research on noise reduction of Larimichthys crocea vocal signals based on improved wavelet threshold-CEEMDAN method
Acoustic signals emitted by large yellow croaker during various stages of breeding period can generally reflect its physiologic-al and behavioral states.However,acoustic signals collected in actual aquaculture environment are often mixed with a variety of noises,so noise reduction pre-processing is required to be performed on raw signals.An improved wavelet threshold-CEEMDAN noise reduc-tion algorithm was proposed,in which original signal was first decomposed into multiple IMFs,then each IMF was processed using im-proved wavelet threshold function,and finally processed IMFs were reconstructed.Results showed that SNR of detection system was in-creased to 14.53 dB and the RMSE was reduced to 0.00196 dB after using noise reduction algorithm proposed.Compared with tradition-al noise reduction algorithms,improved algorithm has a better noise reduction effect,which was more conducive to analyzing and study-ing vocal behaviors during breeding period of large yellow croaker.
large yellow croakerCEEMDANwavelet thresholdingvocal signal processingreproductive monitoring
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