Title

Two-Dimensional Block Adaptive Filtering Algorithms

Abstract

A technique for 2-D system identification which processes 2-D signals using two-dimensional blocks is proposed. Two algorithms which perform 2-D FIR (finite impulse response) adaptive filtering using twodimensional error blocks or windows are presented. The first algorithm uses a convergence factor that is constant for each two-dimensional coefficient at each window iteration. This algorithm is termed as the Two-Dimensional Block Least Mean Square algorithm (TDBLMS). A new 2-D adaptive fast LMS algorithm which processes 2-D signals is presented. In this algorithm, a convergence factor is obtained, that is the same for all 2-D coefficients at a particular window iteration, but is updated at each window iteration. This algorithm is called the Two-Dimensional Optimum Block Algorithm (TDOBA). The above algorithms are also implemented using both disjoint and overlapping signal windows. The convergence properties of the TDBLMS and TDOBA are investigated and compared using computer simulations for both disjoint and overlapping windows. It is shown that the TDOBA clearly outperforms the TDBLMS algorithm with respect to convergence speed and accuracy of adaptation.

Publication Date

1-1-1992

Publication Title

Proceedings - IEEE International Symposium on Circuits and Systems

Volume

3

Number of Pages

1219-1222

Document Type

Article; Proceedings Paper

Identifier

scopus

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ISCAS.1992.230305

Socpus ID

84989435904 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84989435904

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