Anomaly detection of multidimensional and non-stationary process based on q-filtering algorithm
International Journal of Development Research
Anomaly detection of multidimensional and non-stationary process based on q-filtering algorithm
Received 18th June, 2017; Received in revised form 09th July, 2017; Accepted 26th August, 2017; Published online 30th September, 2017
Copyright ©2017, Keyi Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In engineering field,in order to detect the abnormal change of data series in a multidimensional and non-stationary process, an anomaly detection algorithm based on Q-filtering is proposed. Firstly, the Q-filtering algorithm is used to process the multidimensional and non-stationary data series. At the same time, the outlier-tolerant covariance matrix is estimated. Finally, the detection index is used to detect abnormal changes. The algorithm is verified by simulation data and the results show that the algorithm is proved to be have high accuracy and validity.
