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Adaptive filters using modified sliding-block distributed arithmetic with offset binary coding

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2 Author(s)
Walter Huang ; Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, 30332-0250 USA ; David V. Anderson

An efficient way for computing the response of an adaptive digital filter is to use sliding-block distributed arithmetic (SBDA). One disadvantage of distributed arithmetic is the amount of memory utilized. By encoding the memory tables in offset binary code (OBC), the size of the memory tables is reduced in half. However, the computational workload remains unchanged. By modifying the computational flow, the computational workload can be reduced by almost half at the expense of slightly more memory. This modified SBDA structure is called SBDA-OBC. It has memory requirements 25%-50% lower than SBDA depending on the size of the sub-filter. In terms of the computational workload, SBDA-OBC is most advantageous for large sub-filters and when the filter is split into few subfilters. In this case, the computational workload is reduced almost in half.

Published in:

2009 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

19-24 April 2009