Filter plays a major role for removal of unwanted signal/noise from the original signal, especially Adaptive FIR filter is easy to attract for many applications, where it is need to minimize computational requirement. This paper shows a novel pipelined design for low-power, high-throughput, and low-area implementation of adaptive ?lter based on distributed arithmetic (DA). The DA formulation utilized for two separate blocks weight update block and filtering operations requires larger area and is n’t suited for higher order filters therefore causes reduction in the throughput. These issues have been overcome by efficient distributed formulation of Adaptive filters. LMS adaptation performed on a sample by sample basis is replaced by a dynamic LUT update by the weight update scheme. Adder based shift accumulation for inner product computation replaced by conditional signed carry-save accumulation to reduces the sampling period and area density.
Distributed Arithmetic, LMS Adaptive Filter, VHDL, DA, Adaptive Filter, LMS algorithm, Carrysave adder, Noise Cancellation, Digital Signal Processing
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