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Extract EEG Features by Combining Power Spectral Density and Correntropy Spectral Density
2019 Chinese Automation Congress (CAC), 2019The electroencephalogram(EEG)-based brain computer interface (BCI) has been applied to many fields, such as medication, old-age help, transportation and entertainment. How to extract efficient features from low signal to noise ratio (SNR) EEG signals is one of the challenges in EEG signal analysis. In EEG-based BCI systems, power spectral density (PSD)
Xuemei Qin, Yunfei Zheng, Badong Chen
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On the power spectral density of self-synchronizing scrambled sequences
IEEE Transactions on Information Theory, 1998We derive a closed-form expression for the power spectral density of amplitude/phase-shift keyed bit sequences randomized through self-synchronizing scrambling when the source sequence is a stationary sequence of statistically independent bits. In addition to the dependence on the symbol pulse shape, duration, and the signal space values with which ...
Ivan J. Fair +2 more
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Power spectral density limitations of the wavelet-OFDM system
2016 24th European Signal Processing Conference (EUSIPCO), 2016Wavelet-OFDM based on the discrete wavelet transform is a multicarrier modulation technique of considerable interest, due to its good performance in several respects such as the peak-to-average power ratio and the interference cancellation, as investigated in the literature.
Chafii, Marwa +3 more
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Calculation of the power spectral density of the wavefront
SPIE Proceedings, 2000The power spectral density (PSD) was employed to be the specific criterion of the large aperture optical components. Its definition and calculation has analyzed in detail, and the results were given consequently. Furthermore, the calculation of the averaged PSD in different situation is discussed.
Rongzhu Zhang +4 more
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Covariance interpolation and geometry of power spectral densities
2009 European Control Conference (ECC), 2009When methods of moments are used for identification of power spectral densities, a model is matched to estimated second order statistics such as, e.g., covariance estimates. There is an infinite family of power spectra consistent with such an estimate and in applications, such as identification, we want to single out the most representative spectrum ...
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Power spectral density of 3D noise
SPIE Proceedings, 2017When evaluated with a spatially uniform irradiance, an imaging sensor exhibits both spatial and temporal variations, which can be described as a three-dimensional (3D) random process considered as noise. In the 1990s, NVESD engineers developed an approximation to the 3D power spectral density (PSD) for noise in imaging systems known as 3D noise.
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Power Spectral Density and Ride Evaluation
SAE Technical Paper Series, 1966<div class="htmlview paragraph">Vibrational ride environment consists of all motion inputs to the passenger. If each input is properly related to human discomfort, their combined values will produce an overall ride sensation index. This paper presents methods for analyzing and evaluating vibration measurements in an on-the-road environment.
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Modulated Signals and Their Power Spectral Densities
1996Modulation is a process where the message information is embedded into the radio carrier. Message information can be transmitted in the amplitude, frequency, or phase of the carrier, or a combination of these, in either analog or digital form. For mobile radio applications it is desirable to use bandwidth and power resources most efficiently.
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Estimation of the Power Spectral Density Function
2000The power spectrum G(f) of a random process cannot be determined exactly, because measurements can be made only for finite intervals of length T. Therefore, the calculated power spectrum is only an estimate (represented by \( \bar{G}\left( f \right) \) or \( \bar{P}\left( f \right) \) ) and is not identical with the true power spectrum.
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