The invention discloses an electroencephalogram
signal classifying and recognizing method based on a regularized CSP and a regularized SRC and an electroencephalogram
signal remote control system. The method includes the steps of collecting EEG signals produced when n experimenters imagine two different types of movement, and obtaining the
covariance of training data of each experimenter, introducing a regularized parameter alpha and a regularized parameter beta (alpha is larger than or equal to zero and beta is smaller than or equal to one), constructing imagine space filters of two different types of movement, reserving the training data after filtering is conducted, extracting maximum vectors of two types of characteristics, constructing a learning dictionary, inputting test movement imagine data, conducting space filtering, and reserving
test data after filtering is conducted, recognizing the test movement imagine data through a
signal sparse representation method, and determining categories of test samples. The electroencephalogram signal
remote control system comprises a signal collecting module, a signal analyzing module and a controller module. According to the electroencephalogram signal classifying and recognizing method based on the regularized CSP and the regularized SRC and the electroencephalogram signal
remote control system, the electroencephalogram signals are classified and recognized through the regularized CSP and the regularized SRC, the problem of unstable characteristic extraction is effectively solved, and an electroencephalogram signal classifier has stronger robustness compared with an existing classifier.