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Extracting event-related potentials (ERPs) from multichannel EEG recordings remains a challenge due to the poor signal-to-noise ratio (SNR). This paper presents a multivariate statistical model of ERPs by exploiting the existing knowledge about their spatio-temporal properties. In particular, a computationally efficient algorithm is derived for fast model estimation. The algorithm, termed SIM, can...
This paper concerns modulation recognition for blind modulated signals. We use the decision theory, which is popularly used in most researches, to discriminate eleven analog and digital modulated signals with nine key parameters. The carrier frequency is important to calculate some other key parameters. However, for the blind signals, the carrier frequency is unknown, so we propose a method for estimating...
In OFDM systems, carrier frequency offset (CFO) between the transmitter and the receiver destroys the orthogonality among subcarriers and induces strong inter-carrier interference (ICI). For the CFO estimation schemes based on frequency-domain pilot signals, the estimation performance is degraded and bounded by the ICI. In this work we propose a novel CFO estimation scheme - PTA-based with ICI elimination...
Model compensation is an important means to improve the robustness of speaker recognition in noise environment. The robust speaker recognition approach based on model compensation is proposed in this paper. The proposed method combines data reliability estimation and feature components effectiveness estimation, so the errors of the second kind due to the estimation error are reduced greatly. The proposed...
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