17. A system according to claim 13, wherein the parameter estimator is a first parameter estimator, the Markov Model parameters are first Markov Model parameters, and further comprising: a second parameter estimator configured to receive a first training set representing first sequences having a first classification and a second training set representing second sequences, different than the first sequences, having a second classification, and to establish second Markov Model parameters for the second classification based on the first and the second training sets; wherein the classifier is further configured to classify the third sequences based upon the established second Markov Model parameters.
17. A system according to claim 13, wherein the parameter estimator is a first parameter estimator, the Markov Model parameters are first Markov Model parameters, and further comprising: a second parameter estimator configured to receive a first training set representing first sequences having a first classification and a second training set representing second sequences, different than the first sequences, having a second classification, and to establish second Markov Model parameters for the second classification based on the first and the second training sets; wherein the classifier is further configured to classify the third sequences based upon the established second Markov Model parameters. 18. A system according to claim 17, wherein: the first parameter estimator is further configured to generate first Markov Model coefficients associated with the first training set and second Markov Model coefficients associated with the second training set, to adjust the generated first coefficients to be maximally dissimilar to the second coefficients, and to establish the first Markov Model parameters based on the adjusted first coefficients; and the second parameter estimator is further configured to generate third Markov Model coefficients associated with the first training set and fourth Markov Model coefficients associated with the second training set, to adjust the generated fourth coefficients to be maximally dissimilar to the third coefficients, and to establish the second Markov Model parameters based on the adjusted fourth coefficients.