Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 13, Issue 11, Pages 695-698Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2006.879455
Keywords
modeling; pattern classification; signal detection
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The problem of reducing the probability of decision error of an existing binary receiver that is suboptimal using the ideas of stochastic resonance is solved. The optimal probability density function of the random variable that should be ad e to the input is found to be a Dirac delta function, and hence, the optimal random variable is a constant. The constant to be added depends upon the decision regions and the probability density functions under the two hypotheses and is illustrated with an example. Also, an approximate procedure for the constant determination is derived for the mean-shifted binary hypothesis testing problem.
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