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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...
Adaptive filtering constitutes an important class of DSP algorithms employed in several hand held mobile devices for applications such as echo cancellation, signal de-noising, and channel equalization. In this paper, a new hardware architecture using conjugate distributed arithmetic (CDA) which is suitable for high throughput hardware implementations of LMS adaptive filters is presented. Unlike a...
We present a new hardware adaptive filter architecture for very high throughput LMS adaptive filters using distributed arithmetic (DA). DA uses bit-serial operations and look-up tables (LUTs) to implement high throughput filters that use only about one cycle per bit of resolution regardless of filter length. However, building adaptive DA filters requires recalculating the LUTs for each adaptation...
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