2 results about "Inverse system" patented technology

This invention discloses a deep learning-based method for EEG acquisition and analysis, comprising: Step 1: acquiring multi-channel EEG sequences, segmenting them according to time windows, and setting calibration time slots to form segments; Step 2: generating calibration sequences and writing them into the acquisition terminal register within the calibration time slots; Step 3: constructing an input labeled sequence and inputting it into an improved FNet model, outputting link transfer function parameters and contact state vectors; Step 4: performing inverse system reconstruction operations and applying stability constraints to form a reconstructed EEG sequence; Step 5: generating channel-time masks and performing suppression and interpolation to form a clean EEG sequence; Step 6: performing task analysis and processing to form task inference results and calculating a joint credibility index; Step 7: generating and issuing acquisition control command sets. This invention achieves online calibration, stability compensation, and closed-loop adaptive adjustment for EEG acquisition.

The application discloses a kind of unmanned plane angular motion control methods based on incremental local weighting, first based on inverse system idea, the local approximate inverse model of unmanned plane inner loop is constructed, and the control law of unmanned plane inner loop is obtained;Then based on local weighting learning method, the parameter adaptive updating law of unmanned plane inner loop is designed, and the regression parameter is updated, the real-time approximation of local approximate inverse model is realized;Then incremental local weighting method is used to design structure adaptive updating law, and new local approximate inverse model is automatically added when facing unknown characteristic data;Finally, the outer loop controller of the angular motion control of unmanned plane is designed, and the attitude angular velocity command is input to the unmanned plane inner loop;The application utilizes the method that local weighting learning and dynamic inverse are combined to carry out feedback linearization to system, improves the angular motion control precision of unmanned plane, and utilizes incremental local weighting method, and local model is automatically optimized, and the covering of new learning result to original result is avoided.