| 20100217145 | Method of processing multichannel and multivariate signals and method of classifying sources of multichannel and multivariate signals operating according to such processing method - A method of processing multichannel and multivariate signals as described hereinbefore, wherein the signals from each channel are subjected to a first processing step by a recirculation artificial neural network being trained to generate the recorded multichannel and multivariate signals; and a second processing step in which the weights of the connections between the knots of the recirculation neural network determined in the first processing step are processed by an artificial neural network, the recirculation neural network being preferably of the non supervised kind. A particular family of recirculation neural network which can be used according to the present invention is a so called auto-associative neural network. The method further provides, in combination, the use of a predictive and/or classification and/or clustering algorithm for determining the qualities or features of objects from the multichannel multivariate signals generated by said object, the weight matrix obtained by processing said multichannel and multivariate signals with a self-associated neural network being used as records for representing said multichannel and multivariate signals. The method is used for patients suffering from neurological disorders for analysing and evaluating the EEG patterns of these patients. | 08-26-2010 |
