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- W2387996921 abstract "A method for outlier detection based on wavelet HMM( hidden Markov model) is proposed in this paper in order to deal with the inaccurate original data collected from sensors during UUV forecast tracing. The improved recursive wavelet transform( IRWT) is used to reconstruct the original data and locally amplify the wavelet coefficients of the outliers. The update of wavelet coefficients are based on the data at the historical moment,thus,data may be processed in real time by utilizing the difference between normal data and outliers. The judgment function on the distribution of abnormal values is defined by HMM. In addition,on the basis of this,the outliers with features obviously different from the normal data are detected. The quasi-outliers are redetected by using a lazy algorithm for improving the accuracy of the detection results. The data from the lake experiment verify that the method may effectively detect the data outliers in UUV forecast tracing." @default.
- W2387996921 created "2016-06-24" @default.
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- W2387996921 date "2013-01-01" @default.
- W2387996921 modified "2023-09-26" @default.
- W2387996921 title "UUV sensor data outlier detection on the basis of wavelet HMM" @default.
- W2387996921 hasPublicationYear "2013" @default.
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