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However as Mendonça et al. remind, the distinction between noise and signal is not so straightforward but depends on the interpretive context [4].
Here, A s stands for the amplitude of the signal and k 2 stands for the amplitude ratios between noise and signal (A n / A s ).
In [37] the use of random matrix theory (RMT) is suggested to estimate the eigenvalues, whereas in [38] the multiple signal classification (MUSIC) algorithm is used to distinguish between noise and signal space for adaptive threshold placement.
The separation between noise and signal eigenvalues is only clear now in the case of high Signal-to-Noise Ratio (SNR) and low reverberation, when a gap can be clearly observed.
For these lesions, the discrimination between "noise" and "signal" works not very well and the BF produces results for these lesions which are similar to (although not as bad as) those obtained by MAF filtering.
Beyond this value the signal to noise ratio was too low to distinguish between noise and signal.
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The two remaining lesions exhibited a very small elevation of target over background (Δ SUV ≈ 1.5), which reduces the ability of BF to differentiate between noise and true signal, see Discussion.
We used autocorrelation averaging as an alternative way for reducing the observed correlation effect between noise and clean speech signal.
The "decision directed method" provides a trade off between noise reduction and signal distortion when correctly tuned.
First, an artificial neural network is trained to map the relationship between the characteristic, design, noise and signal parameters.
The cut-off frequency for the filter was chosen using the method described on page 42 of Winter, which selects the frequency with the best balance between noise-reduction and signal distortion, using plots of the residuals (i.e. a measure of the difference between the smoothed data and the raw data) (Winter, 1990).
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between noise and song
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