Extending Winograd's Small Convolution Algorithm to Longer Lengths

Simple item page
dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Symposium on Circuits and Systems (ISCAS)en_US
dc.contributor.authorSelesnick, Ivan W.en_US
dc.contributor.authorBurrus, C. Sidneyen_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:04:54Z
dc.date.available2007-10-31T01:04:54Z
dc.date.issued1994-01-15en
dc.date.modified2004-11-11en_US
dc.date.note2004-11-09en_US
dc.date.submitted1994-01-15en_US
dc.descriptionConference Paperen_US
dc.description.abstractFor short data sequences, Winograd's convolution algorithms attaining the minimum number of multiplications also attain a low number of additions, making them very efficient. However, for longer lengths they require a larger number of additions. Winograd's approach is usually extended to longer lengths by using a nesting approach such as the Agarwal-Cooley or Split-Nesting algorithms. Although these nesting algorithms are organizationally quite simple, they do not make the greatest use of the factorability of the data sequence length. The algorithm proposed it this paper adheres to Winograd's original approach more closely than do the nesting algorithms. By evaluating polynomials over simple matrices we retain, in algorithms for longer lengths, the basic structure and strategy of Winograd's approach.en_US
dc.identifier.citationI. W. Selesnick and C. S. Burrus, "Extending Winograd's Small Convolution Algorithm to Longer Lengths," 1994.
dc.identifier.urihttps://hdl.handle.net/1911/20346
dc.language.isoeng
dc.subjectFFT*
dc.subject.keywordFFTen_US
dc.subject.otherFFTsen_US
dc.titleExtending Winograd's Small Convolution Algorithm to Longer Lengthsen_US
dc.typeConference paper
dc.type.dcmiText
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Sel1994Non5ExtendingW.PS
Size:
45.59 KB
Format:
Postscript Files
Download
Collections
ECE Publications
DSP Publications