In this paper, we suggest a simple unsupervised adaptation method of the linear discriminant analysis (LDA) classifier that effectively solves this problem by ...
In this paper we suggest a simple unsupervised adaptation method of the LDA classifier that effectively solves this problem by counteracting the harmful effect ...
A simple unsupervised adaptation method of the linear discriminant analysis (LDA) classifier is suggested that effectively solves this problem by ...
In this paper, we suggest a simple unsupervised adaptation method of the linear discriminant analysis (LDA) classifier that effectively solves this problem by ...
This paper discusses simulated on-line unsupervised adaptation of the LDA classifier in order to counteract the harmful effect of non-class related non- ...
Our results demonstrate that the unsupervised adaptive classiers can improve performance substantially under dierent BCI settings. More importantly, since label ...
In this paper, we suggest a simple unsupervised adap- tation method of the linear discriminant analysis (LDA) classifier that effectively solves this problem by ...
This paper evaluates the advantage of an adaptive classifier based on a Support Vector Machine (SVM) on offline BCI data and shows its benefits and online ...
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The classifier can either be adaptive in a completely unsupervised manner or using unsupervised adaptation in conjunction with a neuronal evaluation signal to ...
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Abstract—In the context of Brain-Computer Interfaces, we propose an adaptive method that reaches offline performance level while being usable online without ...