DocumentCode :
2254157
Title :
The relation of description rate and investment growth rate
Author :
Erkip, Elza ; Cover, Thomas M.
Author_Institution :
Inf. Syst. Lab., Stanford Univ., CA, USA
fYear :
1995
fDate :
17-22 Sep 1995
Firstpage :
73
Abstract :
We have shown that if one invests in the outcome of a random variable X, where investment consists of gambling at any odds, then every bit of description of X increases the doubling rate by one bit. However, if the provider of the information has access only to V, a random variable jointly distributed with X, then this maximal efficiency is not generally possible. We find the increase Δ(R) in doubling rate for a description of V at rate R for the jointly Gaussian and jointly binary cases. We investigate the extension to multivariate Gaussian random variables. We prove a general result for the derivative of Δ(R) at R=0. We then consider the problem in which there are k separate encoders and each observes a random variable Vi correlated with X. We find how efficiently these encoders, without cooperation, help the investor who is interested in X
Keywords :
Gaussian processes; encoding; information theory; random processes; cooperation; description rate; doubling rate; encoders; gambling; investment growth rate; jointly Gaussian cases; jointly binary cases; maximal efficiency; multivariate Gaussian random variables; random variable; Entropy; Information systems; Investments; Labeling; Random variables;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
Conference_Location :
Whistler, BC
Print_ISBN :
0-7803-2453-6
Type :
conf
DOI :
10.1109/ISIT.1995.531175
Filename :
531175
Link To Document :
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