TY - GEN
T1 - Fixed-point-coefficient FIR filters and filter banks
T2 - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007
AU - Heute, U.
AU - Srivastav, A.
AU - Sauerland, V.
AU - Kliewer, J.
PY - 2007
Y1 - 2007
N2 - Frequency-selective, linear-phase FIR filters are considered, as single systems and within analysis-synthesis filter banks. They are usually designed, in the single-channel case, to fulfill tolerances in the Chebychev sense, or, in near-perfect-reconstruction filter banks, to minimize a reconstruction-error measure. If hardware is limited, fixed-point coefficient quantization is needed. It causes, in general, tolerance violations or a larger reconstruction error. Discrete re-optimization may help. A recent technique, able to handle also large filter orders, is successfully applied and newly extended to filter banks. Even better are randomized strategies, introduced and examined in the mathematical-optimization community over the past 15 years; especially, randomized rounding is very effective. Thereby, good results are found for both single-system and ilter-bank designs. We further introduce a new random sub-set selection within the above re-optimization. Like randomized rounding, it allows a trade-off between computational effort and solution quality. Clear improvements over deterministic heuristics are obtained by both randomized algorithms.
AB - Frequency-selective, linear-phase FIR filters are considered, as single systems and within analysis-synthesis filter banks. They are usually designed, in the single-channel case, to fulfill tolerances in the Chebychev sense, or, in near-perfect-reconstruction filter banks, to minimize a reconstruction-error measure. If hardware is limited, fixed-point coefficient quantization is needed. It causes, in general, tolerance violations or a larger reconstruction error. Discrete re-optimization may help. A recent technique, able to handle also large filter orders, is successfully applied and newly extended to filter banks. Even better are randomized strategies, introduced and examined in the mathematical-optimization community over the past 15 years; especially, randomized rounding is very effective. Thereby, good results are found for both single-system and ilter-bank designs. We further introduce a new random sub-set selection within the above re-optimization. Like randomized rounding, it allows a trade-off between computational effort and solution quality. Clear improvements over deterministic heuristics are obtained by both randomized algorithms.
UR - http://www.scopus.com/inward/record.url?scp=51549114764&partnerID=8YFLogxK
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U2 - 10.1109/ISSPA.2007.4555335
DO - 10.1109/ISSPA.2007.4555335
M3 - Conference contribution
AN - SCOPUS:51549114764
SN - 1424407796
SN - 9781424407798
T3 - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
BT - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
Y2 - 12 February 2007 through 15 February 2007
ER -