Blind Identification of MA Models Using Cumulants
| Main Authors: | Mohamed Boulouird, Moha M'Rabet Hassani |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2007
|
| Online Access: |
https://zenodo.org/record/1332558 |
Daftar Isi:
- In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.