摘要
In the present paper, a comparison of the performance between moving cutting data-rescaled range analysis （MC- R/S） and moving cutting data-rescaled variance analysis （MC-V/S） is made. The results clearly indicate that the operating efficiency of the MC-R/S algorithm is higher than that of the MC-V/S algorithm. In our numerical test, the computer time consumed by MC-V/S is approximately 25 times that by MC-R/S for an identical window size in artificial data. Except for the difference in operating efficiency, there are no significant differences in performance between MC-R/S and MC-V/S for the abrupt dynamic change detection. Mc-R/s and MC-V/S both display some degree of anti-noise ability. However, it is important to consider the influences of strong noise on the detection results of MC-R/S and MC-V/S in practical application
In the present paper, a comparison of the performance between moving cutting data-rescaled range analysis （MC- R/S） and moving cutting data-rescaled variance analysis （MC-V/S） is made. The results clearly indicate that the operating efficiency of the MC-R/S algorithm is higher than that of the MC-V/S algorithm. In our numerical test, the computer time consumed by MC-V/S is approximately 25 times that by MC-R/S for an identical window size in artificial data. Except for the difference in operating efficiency, there are no significant differences in performance between MC-R/S and MC-V/S for the abrupt dynamic change detection. Mc-R/s and MC-V/S both display some degree of anti-noise ability. However, it is important to consider the influences of strong noise on the detection results of MC-R/S and MC-V/S in practical application
基金
Project supported by the National Basic Research Program of China(Grant No.2012CB955902)
the National Natural Science Foundation of China(Grant Nos.41275074,41475073,and 41175084)
