On the Epsilon Entropy of Mixed Random Variables

IEEE Transactions on Information Theory

Volumn 34, Issue 5, 1988, Pages 1110-1114

  Rosenthal, Hanan ^a   Binia, Jacob ^b  

^a ROKAR International ^*  (United States)

^b RAFAEL   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION THEORY; MATHEMATICAL TECHNIQUES;

CONTINUOUS RANDOM VARIABLE; EPSILON ENTROPY; MIXED RANDOM VARIABLES; MIXED RANDOM VECTOR; RATE-DISTORTION THEORY;

PROBABILITY;

EID: 0024079299     PISSN: 00189448     EISSN: 15579654     Source Type: Journal    
DOI: 10.1109/18.21244     Document Type: Article

References (7)

1. M. S. Pinsker, Information and Information Stability of Random Variables and Processes. New York: Holden-Day, 1984.
2. C. E. Shannon and W. Weaver, The Mathematical Theory of Communication. Urbana, IL: University of Illinois Press, 1949.
3. T. Berger, Rate Distortion Theory: A Mathematical Basis for Data Compression. Englewood Cliffs, NJ: Prentice-Hall, 1971.
4. J. Binia, M. Zakai, and J. Ziv, “On the ε-entropy and the rate-distortion function of certain non-Gaussian processes,” IEEE Trans. Inform. Theory, vol. IT-20, pp. 517–524, July 1974.
5. A. M. Gerrish and P. M. Schultheiss, “Information rates of non-Gaussian processes,” IEEE Trans. Inform. Theory, vol IT-10, pp. 265–271, Oct. 1964.
6. M. S. Pinsker, “Gaussian sources,” Probl. Peredach. Inform., vol. 14, pp. 59–100, 1963.
7. Y. Baba, “An equality of the quantity of information and its application to the estimate of ε-entropy,” Rep. Faculty Science, Shizuoka Univ., vol. 3, pp. 15–20, 1968.