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Subspace techniques are widely used for direction of arrival (DOA) problems in telecommunications and position location applications for estimating the location of sources from where the signal is originated. This source estimation problem is analogues to the source estimation problem in EEG signal processing commonly termed as EEG inverse problem. The EEG inverse problem goes for estimation of active...
Human brain has a complex structure with the billions of neurons, so it is a difficult and challenging task to predict the behavior of human brain. Different methods and classifiers are used to measure and classify the brain activities with higher accuracy and reliability. In this paper, instead of using mostly used classifier (support vector machine), prediction of the brain activity is done by estimating...
Several methods have been proposed over the past few decades as a solution to the brain sources localization problem using EEG signals. In this paper the performances of different brain source localization techniques, including the Minimum Norm Estimates (MNE), Low Resolution Electrical Tomography (LORETA) and Multiple Sparse Priors (MSP), are assessed and compared. Due to the lack of the baseline,...
A number of techniques have been proposed during the last two decades for Signal-to-Noise Ratio (SNR) estimation in images. The majority of these techniques are based on the cross-correlation function of two images of the same area. However, the need for two images to estimate SNR value confines these techniques to non-stored images and thus limits their applications. In this paper the second order...
In this paper, a novel noise power and SNR estimator based on one OFDM preamble is proposed. The estimator, unlike others, performs noise power estimation at the front-end of the receiver. The proposed estimator is compared with previously published SNR estimators — none of which are front end estimator. The estimator makes use of two identical halves property of time synchronization preamble used...
In this paper, wavelet packet based FFT and its application to SNR estimation is proposed. OFDM systems demodulate data using FFT. The proposed solution computes the exact result, and its computational complexity is same order of FFT, i.e. O(Nlog2 N). SNR estimation is done inside wavelet packet based FFT block unlike previous SNR estimations techniques which perform SNR estimation after FFT. Wavelet...
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