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

  • Authors:

  • Ying-Chang Liang;A.R. Leyman

  • Affiliations:

  • Dept. of Electr. Eng., Maryland Univ., College Park, MD;-

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 1998

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Abstract

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