Title :
A multivariate generalization of Costa’s entropy power inequality
Author :
Payaro, Miquel ; Palomar, Daniel P.
Author_Institution :
Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong
Abstract :
A simple multivariate version of Costapsilas entropy power inequality is proved. In particular, it is shown that if independent white Gaussian noise is added to an arbitrary multivariate signal, the entropy power of the resulting random variable is a multidimensional concave function of the individual variances of the components of the signal. As a side result, we also give an expression for the Hessian matrix of the entropy and entropy power functions with respect to the variances of the signal components, which is an interesting result in its own right.
Keywords :
Hessian matrices; entropy; white noise; Costa entropy power inequality; Hessian matrix; multidimensional concave function; white Gaussian noise; Broadcasting; Degradation; Entropy; Estimation theory; Gaussian noise; Multidimensional systems; Power engineering and energy; Power engineering computing; Random variables; Rate-distortion;
Conference_Titel :
Information Theory, 2008. ISIT 2008. IEEE International Symposium on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-2256-2
Electronic_ISBN :
978-1-4244-2257-9
DOI :
10.1109/ISIT.2008.4595155