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

  • Authors:
  • D. Kazakos

  • Affiliations:
  • -

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2006

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Abstract

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.