http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-104463206-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61F2-72 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24133 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61F2-72 |
| filingDate | 2014-12-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2017-10-20-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2017-10-20-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-104463206-B |
| titleOfInvention | A single motor imagery EEG signal identification method |
| abstract | The invention discloses an identification method of a single motor imagery EEG signal. The identification method includes the following steps: the first step: establishing a single motor imagery EEG signal sample; The covariance matrix of the motor imagery EEG signal samples is preprocessed; the third step: improving the objective function of the matrix Logistic regression algorithm; the fourth step: solving the improved objective function of the third step by accelerating the neighborhood gradient descent method, and obtaining Classifier; the fifth step: using the classifier obtained in the fourth step to classify the imaginary right hand or imaginary foot on the five test sets in the first step, so as to realize the identification of a single motor imagery EEG signal. The identification method can be robust to the non-stationarity of the EEG signal and improve the identification accuracy. |
| priorityDate | 2014-12-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 16.