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The proposed AR parameters estimation technique is based on formulating a particular structured matrix with entries of third order cumulants of the observed output sequence only. This matrix almost possesses a full rank structure. The observed sequence may be contaminated with additive Gaussian noise (white or colored), whose power spectral density is unknown. The system is driven by a zero-mean independent and identically distributed (i.i.d) non-Gaussian sequence. Simulation results confirm the good numerical conditioning of the algorithm and the improvement in performance with respect to well-known methods even when the observed signal is heavily contaminated with Gaussian noise. <\/jats:p>","DOI":"10.1177\/0142331220920482","type":"journal-article","created":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T11:39:22Z","timestamp":1591097962000},"page":"2499-2506","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["A robust method for the identification of non-Gaussian autoregressive systems in colored Gaussian noise"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3796-6805","authenticated-orcid":false,"given":"Adnan","family":"Al-Smadi","sequence":"first","affiliation":[{"name":"Hijjawi Faculty for Engineering Technology, Yarmouk University, 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