Multi-resolution hidden markov model using class specific features

摘要

A method for classifying data includes selecting an elemental size and features for the data that are representative of possible subclasses. Resolution widths are selected in conjunction with these features. Models associated with symbols are developed from these resolution widths and features. Data is compared with these models to give a likelihood that the model applies. The best model is determined and a signal is provided related to the symbol associated with the best model.