000233283 001__ 233283
000233283 005__ 20180913064625.0
000233283 037__ $$aCONF
000233283 245__ $$aOrthonormal realization of fast fixed-order RLS adaptive filters
000233283 269__ $$a2001
000233283 260__ $$c2001
000233283 336__ $$aConference Papers
000233283 520__ $$aThe existing derivations of fast RLS adaptive filters are dependent on the shift structure in the input regression vectors. This structure arises when a tapped-delay line (FIR) filter is used as a modeling filter. In this paper, we show, unlike what original derivations may suggest that fast fixed-order RLS adaptive algorithms are not limited to FIR filter structures. We show that fast recursions in both explicit and array forms exist for more general data structures, such as orthononnally-based models. One of the benefits of working with an orthonormal basis is that fewer parameters can be used to model long impulse responses.
000233283 700__ $$aMerched, Ricardo
000233283 700__ $$0251037$$aSayed, Ali H.$$g283344
000233283 7112_ $$aIEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP$$cSalt Lake City, UT, USA$$dMay 7-11, 2001
000233283 773__ $$j6$$q3789-3792$$tProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP
000233283 909C0 $$0252608$$pASL$$xU13470
000233283 909CO $$ooai:infoscience.tind.io:233283$$pconf$$pSTI
000233283 917Z8 $$x144315
000233283 937__ $$aEPFL-CONF-233283
000233283 970__ $$amerched2001orthonormal/ASL
000233283 973__ $$aOTHER$$rREVIEWED$$sPUBLISHED
000233283 980__ $$aCONF