Method and system for analyzing signal-vector data for pattern recognition from first order sensors

摘要

A method and system of analyzing signal-vector data from first order sensors including providing a training data set, adjusting the training data set using a background adjustment technique, normalizing and transforming the training data set into wavelet coefficients, using an automated analysis of variance feature selection technique and a pattern recognition technique to classify the training data set. The method and system may also include performing these operations on an unknown sample data set collected under unknown conditions and comparing the unknown sample data set to the classification model to provide an identity of the unknown conditions associated with the unknown sample data set. The present invention is also directed to a computer system for analyzing signal-vector data according to this method and a sensing system that includes a sensor and a microprocessor on which is stored a classification model for real-time sensing of unknown sample data sets.