Complexity-constrained LS estimation for sparse systems
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Kocic, M; Brady, D
Published in: IEEE International Symposium on Information Theory - Proceedings
January 1, 1994
In an increasing number of applications the complexity of so-called fast RLS algorithms is prohibitive for real-time RLS estimation. One notable example is the adaptive equalization problem for intersymbol interference channels, where the number of equalizer taps grows linearly with the data rate. Due to the substantial memory in some ISI channels (for example the shallow-water acoustic telemetry channel) the uncoded data rate of real-time telemetry is limited not by the channel distortion or background noise, but by the complexity of the tap update algorithms. © 1994 IEEE.
Duke Scholars
Published In
IEEE International Symposium on Information Theory - Proceedings
DOI
ISSN
2157-8095
Publication Date
January 1, 1994
Start / End Page
116
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Kocic, M., & Brady, D. (1994). Complexity-constrained LS estimation for sparse systems. In IEEE International Symposium on Information Theory - Proceedings (p. 116). https://doi.org/10.1109/ISIT.1994.394872
Kocic, M., and D. Brady. “Complexity-constrained LS estimation for sparse systems.” In IEEE International Symposium on Information Theory - Proceedings, 116, 1994. https://doi.org/10.1109/ISIT.1994.394872.
Kocic M, Brady D. Complexity-constrained LS estimation for sparse systems. In: IEEE International Symposium on Information Theory - Proceedings. 1994. p. 116.
Kocic, M., and D. Brady. “Complexity-constrained LS estimation for sparse systems.” IEEE International Symposium on Information Theory - Proceedings, 1994, p. 116. Scopus, doi:10.1109/ISIT.1994.394872.
Kocic M, Brady D. Complexity-constrained LS estimation for sparse systems. IEEE International Symposium on Information Theory - Proceedings. 1994. p. 116.
Published In
IEEE International Symposium on Information Theory - Proceedings
DOI
ISSN
2157-8095
Publication Date
January 1, 1994
Start / End Page
116