  We propose a new cross-correlation method that can recognize independent
realizations of the same type of stochastic processes and can be used as a new
kind of pattern recognition tool in biometrics, sensing, forensic, security and
image processing applications. The method, which we call bispectrum correlation
coefficient method, makes use of the cross-correlation of the bispectra. Three
kinds of cross-correlation coefficients are introduced. To demonstrate the new
method, six different random telegraph signals are tested, where four of them
have the same power density spectrum. It is shown that the three coefficients
can map the different stochastic processes to specific sub-volumes in a cube.
