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Tracking results Among the earliest works on the tracking performance of adaptive filters are those of Widrow et al (1976) and Bershad et al (1980) The former uses a random-walk model for the variations in the optimal weight vector, while the latter assumes deterministic variations in the optimal weight vector Both works focused on the transient performance of LMS but were not concerned with its steady-state performance Steady-state results appeared subsequently in Farden (1981), Benveniste and Ruget (1982), Walach and Widrow (1984), Eweda and Macchi (1985), Eleftheriou and Falconer (1986), Marcos and Macchi (1987), and Benveniste (1987) The work by Benveniste and Ruget (1982) was apparently the first to compare the tracking performance of different adaptive algorithms More recent analysis for other classes of adaptive filters appear in Eweda (1990b,1994,1997), Hajivandi and Gardner (1990), Cho and Mathews (1990), Guo (1994), Bahai and Sarraf (1997), and Rupp (1998b). vb.net qr code scanner VB . 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The tracking results in Lemma 213 for sign-error LMS agree with those derived by Cho and Mathews (1990) and Eweda (1990b) The tracking results for LMMN are from Yousef and Sayed (1999c,2001) The comparison results of the tracking performance of RLS and LMS agree with those derived by Eweda (1994) Random-walk model It is customary in the literature to use the random-walk model (2010) see, eg, Haykin (2000, p 644)and Macchi (1995) However, as explained in Sec 202, this model is not necessarily meaningful since the covariance matrix of w fgrows unbounded In Robs IV29IV33, we show how to study the tracking performance of adaptive filters by relying instead on model (2014) In the computer project at the end of the chapter, we provide an example that shows how models of the form (2014) arise in applications Random and cyclic nonstationarities. 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