DocumentCode
2264974
Title
Achievable rates for pattern recognition: binary and Gaussian cases
Author
Westover, M. Brandon ; O´Sullivan, Joseph A.
Author_Institution
Dept. of Phys., Washington Univ., St. Louis, MO
fYear
2005
fDate
4-9 Sept. 2005
Firstpage
28
Lastpage
32
Abstract
Recently we presented information-theoretic bounds for the achievable rates of pattern recognition systems operating under data compression constraints. In this paper we improve on our previous inner bound, and report progress toward finding formulas for the achievable rate region boundaries in the special cases where the pattern data is either binary or Gaussian
Keywords
Gaussian processes; data compression; information theory; pattern recognition; Gaussian data; binary data; data compression constraints; information-theoretic; pattern recognition; Computer aided software engineering; Data compression; Data engineering; Information theory; Memoryless systems; Pattern recognition; Physics; Probability distribution; System testing; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2005. ISIT 2005. Proceedings. International Symposium on
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-9151-9
Type
conf
DOI
10.1109/ISIT.2005.1523286
Filename
1523286
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