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(Almost) periodic moving average system identification using higher order cyclic-statistics

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2 Author(s)
Ying-Chang Liang ; Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA ; A. R. Leyman

This article addresses the problem of (almost) periodic moving average (APMA) system identification. Two new normal equations relating the coefficients of an APMA system and the time-varying higher order cumulants of the measurements are established, from which two new linear algebraic algorithms are presented for system parameter estimation. In addition, a new singular value decomposition (SVD) based algorithm is proposed for determining the system order. Simulation examples are given to demonstrate the performance of these new approaches

Published in:

IEEE Transactions on Signal Processing  (Volume:46 ,  Issue: 3 )