Testing the independence of two non-stationary random processes with applications to biometric authentication

We present an algorithm for testing the independence of two non-stationary random processes, which is based on the transformation of realizations of the processes to q-ary vectors whose components are uniformly distributed over the set {0,..., q - 1}. An application of the algorithm to the biometric authentication problem brings the false acceptance rate that does not depend on the probability distribution over the templates space and exponentially decreases with the number of independent biometric parameters available to an observer.