TY - GEN

T1 - Mutual information and conditional mean estimation in poisson channels

AU - Guo, Dongning

AU - Verdú, Sergio

AU - Shamai, Shlomo

PY - 2004

Y1 - 2004

N2 - Following the recent discovery of new connections between information and estimation in Gaussian channels, this paper reports parallel results in the Poisson regime. Both scalar and continuous-time Poisson channels are considered. It is found that, regardless of the statistics of the input, the derivative of the input-output mutual information with respect to the dark current can be expressed in the expected difference between the logarithm of the input and the logarithm of its conditional mean estimate (noncausal in case of continuous-time). The same is true for the derivative with respect to input scaling, but with the logarithmic function replaced by x log x.

AB - Following the recent discovery of new connections between information and estimation in Gaussian channels, this paper reports parallel results in the Poisson regime. Both scalar and continuous-time Poisson channels are considered. It is found that, regardless of the statistics of the input, the derivative of the input-output mutual information with respect to the dark current can be expressed in the expected difference between the logarithm of the input and the logarithm of its conditional mean estimate (noncausal in case of continuous-time). The same is true for the derivative with respect to input scaling, but with the logarithmic function replaced by x log x.

UR - http://www.scopus.com/inward/record.url?scp=17644382199&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=17644382199&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:17644382199

SN - 0780387201

T3 - 2004 IEEE Information Theory Workshop - Proceedings, ITW

SP - 265

EP - 270

BT - 2004 IEEE Information Theory Workshop - Proceedings, ITW

T2 - 2004 IEEE Information Theory Workshop - Proceedings, ITW

Y2 - 24 October 2004 through 29 October 2004

ER -