document: A new architecture for implementing pipelined FIR ADF based on classification of coefficients In this paper , we propose a new method for implementing pipelined finite-impulse response -LRB- FIR -RRB- adaptive digital filter -LRB- ADF -RRB- , with an aim of reducing the maximum delay of the filtering portion of conventional delayed least mean square -LRB- DLMS -RRB- pipelined ADF . We achieve a filtering section with a maximum delay of one by simplifying a pre-upsampled and a post-downsampled FIR filter using the concept of classification of coefficients . This reduction is independent of the order of the filter , which is an advantage when the order of the filter is very large , and as a result the method can also be applied to infinite impulse response -LRB- IIR -RRB- filters . Furthermore , when the proposed method is compared with the transpose ADF , which has a filtering section with zero delay , it is realized that it significantly reduces the maximum delay associated with updating the coefficients of FIR ADF . The effect of this is that , the proposed method exhibits a higher convergence speed in comparison to the transpose FIR ADF
doc_bio_tags: O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O
extractive_keyphrases: pipelined fir adf adaptive digital filter maximum delay convergence speed
abstractive_keyphrases: coefficient classification delayed least mean square filter pre-upsampled filter post-downsampled filter