Abstract—In this paper, a two-dimensional (2-D) version of
the recently proposed second order Recursive Inverse (2nd
order RI) algorithm is introduced. In the proposed algorithm,
instead of estimating the inverse autocorrelation matrix, a
second order estimate of the autocorrelation matrix and cross
correlation vector, which provide an improved and a more
stable performance, are used. Also, the filter coefficients are
updated along both the horizontal and vertical directions on a
2-D plane. The performance of the proposed algorithm is
compared to that of the 2-D RLS algorithm in Adaptive Line
Enhancer (ALE) problem. Simulation results show that the
proposed algorithm leads to an improved performance
compared to that of the 2-D RLS algorithm.
Index Terms—2-D RLS, adaptive filters, ALE.
M. S. Salman is with the department of Electrical & Electronic
Engineering, Mevlana (Rumi) University, Selcuklu, Konya, Turkey (e-mail:
mssalman@mevlana.edu.tr).
A. Hocanin and O. Kukrer are with the department of Electrical &
Electronic Engineering, Eastern Mediterranean University, Gazimagusa,
TRNC, via Mersin 10, Turkey (e-mail: aykut.hocanin@emu.edu.tr,
osman.kukrer@emu.edu.tr).
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Cite:Mohammad Shukri Salman, Aykut Hocanin, and Osman Kukrer, "A 2-D Second-Order Recursive Inverse Adaptive Filtering Algorithm," International Journal of Computer Theory and Engineering vol. 6, no. 1, pp. 1-3, 2014.
