the volterra model is widely used for nonlinearity identification in practical applications. in this paper, we employed volterra model to find the nonlinearity relation between electroencephalogram (eeg) signal and the noise that is a novel approach to estimate noise in eeg signal. we show that by employing this method. we can considerably improve the signal to noise ratio by the ratio of at le...

in this paper, a new approach based on game theory has been proposed to multi responses problem optimization. game theory is a useful tool for decision making in the conflict of interests between intelligent players in order to select the best joint strategy for them through selecting the best joint desirability. present research uses the game theory approach via definition of each response as ...

Of the many measures that characterize the performance of a communication receiver, signal-to-noise ratio (SNR) is perhaps the most fundamental in that many of the other measures directly depend on its knowledge for their evaluation. In the design of receivers for autonomous operation, it is desirable that the estimation of SNR take place with as little known information as possible regarding o...

Signal-to-noise ratio, the ratio between signal and noise, is a quantity that has been well established for MRI data but is still subject of ongoing debate and confusion when it comes to fMRI data. fMRI data are characterised by small activation fluctuations in a background of noise. Depending on how the signal of interest and the noise are identified, signal-to-noise ratio for fMRI data is rep...

objective(s): in spect, the sinogram contains scatter and lack of attenuated counts that degrade the reconstructed image quality and quantity. many techniques for attenuation and scatter correction have been proposed. an acceptable method of correction is to incorporate effects into an iterative statistical reconstruction. here, we propose new maximum likelihood expectation maximization (mlem) ...