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To address the nonstationarity issue in EEG-based brain computer interface (BCI), the computational model trained using the training data needs to adapt to the data from the test sessions. In this paper, we propose a novel adaptation approach based on the divergence framework. Cross-session changes can be taken into consideration by searching the discriminative subspaces for test data on the manifold...
We generalize the convergence, the stability and the averaged converging rate of stochastic parallel gradient descent algorithm when it is used as control algorithm for adaptive optics system in theory. Analysis results show the adaptive optics system can obtain convergence, stability and a factor of n /square root (n is the number of control parameters) speeding compared with sequential gradient...
Optimizing the system performance metric directly is an important method for correcting wave-front distortions in adaptive optics(AO) systems. Appropriate stochastic parallel optimization control algorithm is the key to correcting distorted wave front successfully. Based on several stochastic parallel optimization control algorithms, an adaptive optics system with a 32-element deformable mirror was...
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