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Abnormal Signal Detection Method Based on Heavy-tailed Distribution


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Abnormal Signal Detection Method Based on Heavy-tailed Distribution
WANG Li-li12LIU Li-wei3XIONG Yan-ye1
1. Scientific Researching Department,Naval Command College,Nanjing 210016,China; 2. Institute of Command Automation,PLA University of Science and Technology,Nanjing 210007,China; 3. School of Sciences,NUST,Nanjing 210094,China
expectation maximization algorithm maximum likelihood estimation Cook distance Q function abnormal signals
In order to detect the abnormal signals with a heavy tailed distribution,the statistical diagnosis method based on expectation maximization( EM) algorithm is applied to abnormal signal detection for normal inverse Gaussian signal. To avoid the difficulties of calculating Bessel functions, the normal inverse Gaussian signal is treated as missing data. The maximum likelihood estimation of parameters is obtained using the EM algorithm,simplifying the calculation. The Q function takes place of the log-likelihood function and a Q-based measurement for the diagnosis method of normal inverse Gaussian distribution is proposed. The results of the calculation example and computer simulation demonstrate the superiority of the methods proposed here.


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Last Update: 2012-02-28