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Topic

Noise spectral density

About: Noise spectral density is a(n) research topic. Over the lifetime, 8614 publication(s) have been published within this topic receiving 149505 citation(s).


Papers
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Journal ArticleDOI
01 Feb 1966

2,325 citations

Journal ArticleDOI
TL;DR: The image intensity in magnetic resonance magnitude images in the presence of noise is shown to be governed by a Rician distribution and low signal intensities (SNR < 2) are therefore biased due to the noise.
Abstract: The image intensity in magnetic resonance magnitude images in the presence of noise is shown to be governed by a Rician distribution. Low signal intensities (SNR < 2) are therefore biased due to the noise. It is shown how the underlying noise can be estimated from the images and a simple correction scheme is provided to reduce the bias. The noise characteristics in phase images are also studied and shown to be very different from those of the magnitude images. Common to both, however, is that the noise distributions are nearly Gaussian for SNR larger than two.

2,253 citations

Proceedings ArticleDOI
02 Apr 1979
TL;DR: This paper describes a method for enhancing speech corrupted by broadband noise based on the spectral noise subtraction method, which can automatically adapt to a wide range of signal-to-noise ratios, as long as a reasonable estimate of the noise spectrum can be obtained.
Abstract: This paper describes a method for enhancing speech corrupted by broadband noise. The method is based on the spectral noise subtraction method. The original method entails subtracting an estimate of the noise power spectrum from the speech power spectrum, setting negative differences to zero, recombining the new power spectrum with the original phase, and then reconstructing the time waveform. While this method reduces the broadband noise, it also usually introduces an annoying "musical noise". We have devised a method that eliminates this "musical noise" while further reducing the background noise. The method consists in subtracting an overestimate of the noise power spectrum, and preventing the resultant spectral components from going below a preset minimum level (spectral floor). The method can automatically adapt to a wide range of signal-to-noise ratios, as long as a reasonable estimate of the noise spectrum can be obtained. Extensive listening tests were performed to determine the quality and intelligibility of speech enhanced by our method. Listeners unanimously preferred the quality of the processed speech. Also, for an input signal-to-noise ratio of 5 dB, there was no loss of intelligibility associated with the enhancement technique.

1,296 citations

Journal ArticleDOI
Abstract: A general expression is derived from which the spectral density of the noise generated in a uniformly multiplying p-n junction can be calculated for any distribution of injected carriers. The analysis is limited to the white noise part of the noise spectrum only, and to diodes having large potential drops across the multiplying region of the depletion layer. It is shown for the special case in which \beta = k\alpha , where k is a constant and α and β are the ionization coefficients of electrons and holes, respectively, that the noise spectral density is given by 2eI_{in}M^{3}[1 + (\frac{1 - k}{k})(\frac{M - 1}{M})^{2}] where M is the current multiplication factor and I in the injected current, if the only carriers injected into the depletion layer are holes, and by 2eI_{in}M^{3}[1 - (1 - k)(\frac{M - 1}{M})^{2}] if the only injected carriers are electrons. An expression is also derived for the noise power which will be delivered to an external load for the limit M \rightarrow \infin .

1,243 citations

Book
01 Jan 1986
Abstract: Mathematical Methods Noise Characterization Noise Measurements Thermal Noise Shot Noise Generation - Recombination Noise Flicker Noise or 1/f Noise Noise in Particular Amplifier Circuits Mixers Miscellaneous Problems Appendixes Index.

1,125 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20221
202141
202050
201962
201869
2017180