Sufficiency, classification, and the class-specific feature theorem

IEEE Transactions on Information Theory

Volumn 46, Issue 4, 2000, Pages 1654-1658

  Kay, Steven ^a  

^a The University of Rhode Island   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION THEORY; MATHEMATICAL MODELS; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION; SIGNAL DETECTION; VECTORS;

BAYES PROCEDURE; CLASS SPECIFIC FEATURE THEOREM; PARAMETER VECTOR;

THEOREM PROVING;

EID: 0034226244     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/18.850711     Document Type: Article

References (8)

1. A. C. Atkinson, A method for discriminating between models, J. Roy. Statist. Soc., vol. 32, pp. 323-353, 1970.
2. P. Baggenstoss, Class-specific feature sets in classification, IEEE Trans. Signal Processing, vol. 47, pp. 3428-3432, Dec. 1999.
3. S. Kay, Fundamentals of Statistical Signal Processing, Vol. I: EstimationTheory. Englewood Cliffs, NJ: Prentice-Hall, 1993, Appendix 5A.
4. _, Fundamentals of Statistical Signal Processing, Vol. 2: Detection Theory. Upper Saddle River, NJ: Prentice-Hall, 1998.
5. M. Kendall and A. Stuart, The Advanced Theory of Statistics, Vol. 11. New York: Macmillan, 1977.
6. S. Kullback, Information Theory and Statistics. New York: Dover, 1968, pp. 19-20.
7. D. W. Scott, Multivariate Density Estimation. New York: Wiley, 1992.
8. S. Zacks, The Theory of Statistical Inference. New York: Wiley, 1971.