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This paper describes the method for classifying multiclass motor imagery EEG signals of brain-computer interfaces (BCIs) according to the phenomena of event-related desynchronization and synchronization (ERD/ERS). The method of one-versus-one common spatial pattern (CSP) for multiclass feature extraction was employed. And we extended two different kinds of classifiers: 1) support vector machines (SVM)...
Brain-computer interface (BCI) system uses brain activity to control external devices such as computers and electronic devices. It is a novel kind of human computer interaction. BCI system can be regard as pattern recognition system, and the key point is classification of Electroencephalogram (EEG) signals under different mental tasks. Classification algorithms of BCI system include Fisher linear...
Steganalysis is taken as a countermeasure to steganography and is detecting and decoding hidden data within a given media. There has been quite some effort in audio steganalysis for additive embedding model. However, when they distinguish the cover-audio signal with multiplicative noise and the stego-audio signal, results are disappointing. In this paper, a wavelet domain audio steganalysis method...
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