By Topic

Spectral distance measures between continuous-time vector Gaussian processes (Corresp.)

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)

A new expression for the Chernoff distance between two continuous-time stationary vector Gaussian processes that contain a common white noise component and have equal means is derived. The expression is given in terms of the spectral density matrices for large observation intervalT. The expression is then used for deriving upper and lower bounds to the Bayes probability of error. Both bounds converge to zero exponentially inT. It is also shown that theI-divergence andJ-divergence can be easily evaluated in the frequency domain by differentiation of the Chernoff distance.

Published in:

Information Theory, IEEE Transactions on  (Volume:28 ,  Issue: 4 )