A fast-implemented recursive inverse adaptive filtering algorithm - Salman, Mohammad Shukri; Hocanin, Aykut; Kukrer, Osman (My University, 2010)
The recently proposed Recursive Inverse (RI) adaptive algorithm [1] has shown improved performance in channel equalization and system identification settings. Although its computational complexity is lower than those of the RLS and Robust RLS algorithms, its computational complexity can be reduced further. A fast implementation method is applied in this paper to decrease its computational complexity. The performance of the fast implemented RI algorithm is compared to those of the Variable Step-Size LMS (VSSLMS), Discrete Cosine Transform LMS (DCTLMS) and Recursive-Least-Squares (RLS) algorithms in Additive White Gaussian Noise (AWGN), Additive Correlated Gaussian Noise (ACGN), Additive White Impulsive Noise (AWIN) and Additive Correlated Impulsive Noise (ACIN) environments in a noise cancellation setting. Simulation results show that the Fast RI algorithm performs better than the VSSLMS and DCTLMS algorithms. Its performance is the same as in the RLS algorithm with a considerable reduction in complexity. ©2010 IEEE.
Hizlandirilmiş özyineli evrik uyarlanir süzgeç algoritmasi
18th IEEE Signal Processing and Communications Applications Conference, SIU 2010 --
Keywords: Adaptive filtering algorithms; Additive White Gaussian noise; Correlated Gaussian noise; Fast implementation; Impulsive noise; In-channels; Noise cancellation; Recursive least squares; RLS algorithms; Simulation result; System identifications; Variable step-size LMS; Adaptive filtering; Adaptive filters; Computational complexity; Cosine transforms; Discrete cosine transforms; Gaussian noise (electronic); Impulse noise; Signal processing; White noise; Adaptive algorithms