Parameter Estimation and Time-frequency Distribution of Fractional Lower Order Time-frequency Auto-regressive Moving Average Model Algorithm Based on SαS Process
LONG Junbo① WANG Haibin②
①(College of Electronic and Engineering, Jiujiang University, Jiujiang 332005, China) ②(College of Information Science and Technology, Jiujiang University, Jiujiang 332005, China)
The performances of Time-Frequency Auto-Regressive Moving Average (TFARMA) model method degenerate under SS distribution environment. Hence, Fractional Lower Order Time-Frequency Auto- Regressive Moving Average (FLO-TFARMA) model algorithm based on fractional lower order covariant is proposed, the parameters estimation of FLO-TFARMA model is introduced, time-frequency distribution based on FLO-TFARMA model is given, FLO-TFARMA model algorithm are compared with the existing TFARMA algorithm in detail. The simulation results show that FLO-TFARMA model method have better performance than TFARMA model method under SαS distribution environment, and the time-frequency spectrum of FLO- TFARMA method is more obvious when the parameter α is smaller.
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LONG Junbo, WANG Haibin. Parameter Estimation and Time-frequency Distribution of Fractional Lower Order Time-frequency Auto-regressive Moving Average Model Algorithm Based on SαS Process. JEIT, 2016, 38(7): 1710-1716.
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