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# Topic: Gaussian noise

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 Gaussian noise - Wikipedia, the free encyclopedia Gaussian noise is noise that has a probability density function (pdf) of the normal distribution (a.k.a. Gaussian noise is properly defined as noise with a Gaussian amplitude distribution. Gaussian noise is sometimes misunderstood to be white gaussian noise, but this is not the case. en.wikipedia.org /wiki/Gaussian_noise   (139 words)

 White noise - Wikipedia, the free encyclopedia The term white noise is also commonly applied to a noise signal in the spatial domain which has zero autocorrelation over the relevant space dimensions. Gaussianity refers to the way signal values are distributed, while the term 'white' refers to correlations at two distinct times, which are independent of the noise amplitude distribution. White noise has also been used in electronic music, where it is used either directly or as an input for a filter to create other types of noise signal. en.wikipedia.org /wiki/White_noise   (1586 words)

 Additive white Gaussian noise - Wikipedia, the free encyclopedia In communications, the additive white Gaussian noise (AWGN) channel model is one in which the only impairment is the linear addition of wideband or white noise with a constant spectral density (expressed as watts per hertz of bandwidth) and a Gaussian distribution of amplitude. Wideband Gaussian noise comes from many natural sources, such as the thermal vibrations of atoms in antennas, fl body radiation from the earth and other warm objects, and from celestial sources such as the sun. It is not a good model for most terrestrial links because of multipath, terrain blocking, interference, etc. However for terrestrial path modeling, AWGN is commonly used to simulate background noise of the channel under study, in addition to multipath, terrain blocking, interference, ground clutter and self interference that modern radio systems encounter in terrestrial operation. en.wikipedia.org /wiki/Additive_white_gaussian_noise   (258 words)

 The Gaussian Processes Web Site The simplest uses of Gaussian process models are for (the conjugate case of) regression with Gaussian noise. Gaussian processes are in my view the simplest and most obvious way of defining flexible Bayesian regression and classification models, but despite some past usage, they appear to have been rather neglected as a general-purpose technique. We derive novel analytic expressions for the predictive mean and variance for Gaussian kernel shapes under the assumption of a Gaussian input distribution in the static case, and of a recursive Gaussian predictive density in iterative forecasting. www.gaussianprocess.org   (10052 words)

 Random Electrical Noise: A Literature Survey To verify that a noise source is indeed producing thermal noise, it may be useful to "short out" the source resistance and verify a marked reduction in resulting noise (hopefully to under 1/10 of the original value). Thus, the noise is identical to shot noise associated with a dc current twice as large as the reverse saturation current of the diode. The noise seems to be generated by a noise current generator in parallel with the dynamic resistance of the diode." (p. www.ciphersbyritter.com /RES/NOISE.HTM   (8483 words)

 white noise all on one page F fwhite noise, fewwhite noise, fiftywhite noise, firstwhite noise, fivewhite noise, forwhite noise, formerwhite noise, formerlywhite noise, fortywhite noise, foundwhite noise, white noise, fourwhite noise, fromwhite noise, furtherwhite noise. N nwhite noise, namelywhite noise, neitherwhite noise, neverwhite noise, neverthelesswhite noise, nextwhite noise, ninewhite noise, ninetywhite noise, nowhite noise, nobodywhite noise, nonewhite noise, nonethelesswhite noise, noonewhite noise, norwhite noise, notwhite noise, nothingwhite noise, nowwhite noise, nowherewhite noise. C htppwhite noise www.white noise.com www.white noise.com www.white noise com wwwwhite noise.com wwwhite noise.com wwwwwhite noise.com www.white noise.comm wwwwhite noisecom wwwwwhite noisecom wwwhite noise.com c, white noisecan, white noisecan't, white noisecannot, white noisecaption, white noiseco, white noiseco., white noisecould, white noisecouldn't. seindex.fcpages.com /white-noise.html   (747 words)

 Gaussian_Noise   (Site not responding. Last check: 2007-10-08) Other examples occur with some types of radio tubes or semi-conductors where the noise may be amplified to produce a noise generator. Note that in all of these cases, it is only the signal's amplitude fluctuating randomly that results in its being classified as Gaussian noise. Gaussian distribution showing the probability y of finding a deviation x from the mean (x = 0), according to the equation stated, where e is the base of natural logarithms, and www.sfu.ca /sonic-studio/handbook/Gaussian_Noise.html   (220 words)

 GNG -- Gaussian Noise Generation   (Site not responding. Last check: 2007-10-08) GNG is used to test the robustness of various image analysis algorithms (such as classifiers, filters, transforms, etc.) in the presence of noise. GNG generates Gaussian noise and adds it to a specified set of output image channels on the database (DBOC). Add random Gaussian noise (with a mean of 0 and 34% of the additive noise in the grey level range 0-3) to an existing image channel. www.pcigeomatics.com /cgi-bin/pcihlp/GNG   (347 words)

 [No title] The noise is modeled as a mixture of Gaussian distributions, and the expectation-maximization (EM) algorithm is used to derive estimates for the model parameters. The details of the signal and noise environment are explained in \cite{dretar}, but the key result is that the BER of the maximal ratio combiner does not improve, and thus remains poor, as more antennas are added, while the new receiver performs better with each new antenna that is added. Note that Gaussian noise is a special case of the Gaussian mixture pdf, so our receiver is capable of adapting to Gaussian noise and performing the linear processing that is optimum. www.eecs.lehigh.edu /SPCRL/AR/AR   (2141 words)

 Spatial Filters - Gaussian Smoothing   (Site not responding. Last check: 2007-10-08) The idea of Gaussian smoothing is to use this 2-D distribution as a `point-spread' function, and this is achieved by convolution. In theory, the Gaussian distribution is non-zero everywhere, which would require an infinitely large convolution kernel, but in practice it is effectively zero more than about three standard deviations from the mean, and so we can truncate the kernel at this point. The effect of Gaussian smoothing is to blur an image, in a similar fashion to the mean filter. homepages.inf.ed.ac.uk /rbf/HIPR2/gsmooth.htm   (1121 words)

 Robust Regression with online Gaussian Processes The estimation was compared with Gaussian noise assumption, thus involving three models for the likelihood function for which we can estimate the noise (see the EM algorithm from the previous section). The algorithm estimates the length-scale and amplitude of the GP kernel (model parameters) and the noise of the likelihood. 1, the algorithm estimates the length-scale and amplitude of the GP kernel (model parameters) and the noise of the likelihood. www.ncrg.aston.ac.uk /Projects/SSGP/examples/robust/robust.html   (784 words)

 Image Synthesis - Noise Generation Noise are random background events which have to be dealt with in every system processing real signals. Another common form of noise is data drop-out noise (commonly referred to as intensity spikes, speckle or salt and pepper noise). The noise is usually quantified by the percentage of pixels which are corrupted. www.cee.hw.ac.uk /hipr/html/noise.html   (1072 words)

 CSE/EE 486:  Fundamentals of Computer Vision   (Site not responding. Last check: 2007-10-08) Gaussian noise of zero mean and standard deviation of 5 was generated. Gaussian filtering was implemented by generating a 5x5 Gaussian mask with standard deviation 1 by using the formula e^[-(h^2+k^2)/(2)]: The gaussian filter acted similar to the mean filter, but did not blur the pictures as much. www.cse.psu.edu /~ago/486/proj2/report.html   (1082 words)

 DaqGen - Gaussian Noise Gaussian noise is really "white", just like the White noise source, in the sense that it has equal energy at all frequencies. Note that in one respect this Gaussian source does not provide a "true" Gaussian normal distribution, and you should be glad of that: The true Gaussian requires values that extend to infinity in both directions, even though they might be very infrequent. The central peak of the histogram is thus proportionally higher, and all features of the Gaussian curve are constricted toward the center by the same proportion. www.daqarta.com /DG_VV0G.HTM   (962 words)

 Electronics - Wikipedia, the free encyclopedia Noise is generally defined as any unwanted signal that is not present at the input of the circuit. Noise is not the same as distortion caused by the circuit. Mathematical methods are integral to the study of electronics. en.wikipedia.org /wiki/Electronics   (1195 words)

 BACKGROUND   (Site not responding. Last check: 2007-10-08) For comparison of noise among measurements at different applied current levels, it is more convenient to use the first spectrum normalized by the squared d.c. Gaussian fluctuations are expected to have stationary second spectra, and so in the cases of the Johnson and Gaussian 1/f noise backgrounds the expectation values of If noise is a probe of the microstructural dependence of local current flow, then changes in the noise statistics of the dark conductivity after light exposure should yield information about the validity of the current microfilament picture. www.physics.nyu.edu /~dg86/secspec2b/node1.html   (1282 words)

 Weakly Non-Gaussian Processes in a-Si:H Conductance Noise The effects upon the noise of annealing and aging the sample as well as the time evolution of the second spectrum upon application of an electrical field suggest that sample microstructure and field induced processes may play roles in inducing correlations among fluctuators. The differences between periods of RTSN and periods of flicker noise thus are revealed to be differences in the relative importance of phase-correlated processes to overall noise production. The details of the experimental setup for collecting noise data on a-Si:H samples are described in Section II, and the results of applying the signal analysis techniques discussed in Section I to several representative noise measurements are presented in Section III. www.physics.nyu.edu /~dg86/secspec2b/secspec2b.html   (522 words)

 No Title The variance of the noise, gaussian, function at the output of the reciever may be calculated assuming zero mean as : Assume that the noise voltage at the output is v Because we have Gaussian noise, the probability of the noise voltage is : www.eeng.dcu.ie /~murphyj/ee4/ee4part3/ee4part3.html   (1081 words)

 Detection of Weak Random Signals in IID Non-Gaussian Noise   (Site not responding. Last check: 2007-10-08) However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. The analytical expressions are used to evaluate the robustness of detectors to mismatch in the noise models. nonlinearities are nearly optimum and robust to modest errors in the noise statistics. www.comsoc.org /comm/private/2000/feb/222_48comm02-kolodziejski.html   (327 words)

 Extra Problems for Chapter 10 Consider a Gaussian noise channel of power contraint P, where the signal takes two different paths and the received noisy signals are added together at the antenna. Extend the result to the case where the noise is not iid but is stationary and ergodic with power N. Thus Z has a mixture distribution which is the mixture of a Gaussian distribution and a degenerate distribution with mass 1 at 0. www-isl.stanford.edu /~jat/eit2/webbook/exch10/exch10.html   (772 words)

 Eingang zum Volltext The content of this thesis is as follows: In the first two chapters I give a short introduction to wavelets and their use in non-parametric function estimation. The fourth chapter deals with the function space approach: an addition to known results is obtained and the performance of wavelet thresholding for median filtered data is investigated. The subject of chapter 5 is an extension of Stein's unbiased risk estimation for general classes of infinitely divisible noise in the location model. www.freidok.uni-freiburg.de /volltexte/10   (325 words)

 [No title] As in the white noise case, the important signal-related quantity in this expression is the signal-to-noise ratio of the difference signal. The size of the noise covariance matrix, equal to the number of observations used by the detector, is usually large: hundreds if not thousands of samples are possible. The lower diagram is often termed the whitening filter structure, where the noise components of the observed data are first whitened, then passed through a matched filter whose unit-sample response is related to the "whitened" signal. cnx.rice.edu /content/m11260/1.2/source   (1179 words)

 Your source for Gaussian noise source information The term Gaussian means that the probability density function is random and follows a bell curve. The output specifications of the noise circuit are dependent on two variables, the characteristic of the noise diode itself and the biasing circuit. The ability to shape the noise amplitude spectrally is an art as much as it is science in that the years of collective experience helps a design team immensely for producing a desired output. www.noisesources.com   (356 words)

 Sorption-cooler noise.   (Site not responding. Last check: 2007-10-08) The amplitude of the systematic is smaller in the case with the correlated Gaussian noise by nearly an order of magnitude due to the high Gaussian noise level in those modes, ``weighting-out'' the low frequency modes of the stream. component of the noise is a result of the noise-weighting which decreases the relative importance of the low-frequency modes. The green line shows the spectrum of the Gaussian noise only and the red line - the spectrum of the SC+Gaussian noise time stream projected on the sky, however, with the piece-wise constant offset and drift removed from the map during the sky projection (map-making) procedure. astron.berkeley.edu /~radek/planck_summary_online/node13.html   (719 words)

 ☞ reference - additive white gaussian noise - additive white gaussian noise online guide   (Site not responding. Last check: 2007-10-08) Adding noise is not the most useful thing in most DSP applications, but it is awfully useful for test suites. Gaussian white noise has the useful statistical property that its values are... Non-Data-Aided Parameter Estimation in an Additive White Gaussian Noise Channel Non-Data-Aided Parameter Estimation in an Additive White Gaussian Noise Channel Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-... www.reference123.info /whitenoise/additive-white-gaussian-noise.html   (730 words)

 Introduction Impulsive noise occurs in indoor and outdoor environments due to a variety of sources [3, 4]. Middleton and others [7, 8] have shown that the Gaussian mixture distribution model is accurate for many impulsive noise environments, while Redner and Walker [9] and others [10] have shown that the EM algorithm has attractive computational features when applied to Gaussian mixture distributions. The details of the signal and noise environment are explained in [6], but the key result is that the BER of the maximal ratio combiner does not improve, and thus remains poor, as more antennas are added, while the new receiver performs better with each new antenna that is added. www.eecs.lehigh.edu /SPCRL/AR/node1.html   (444 words)

 Noise Generator 1/f noise is very common in nature, and can be used to model phenomenon as disparate as the curvature of a beach to the volume produced by a symphony orchestra to the spectrum of noise from almost all semiconductor devices at low enough frequencies. The prevalence of 1/f noise is one of the deep ques-tion about our world, but nobody has a good explanation. Shot noise is also called counting or Poisson noise, and occurs whenever as an average number of samples is supposed to arrive in a fixed time interval. ist-socrates.berkeley.edu /~phylabs/bsc/Supplementary/NoiseGenerator.html   (616 words)

 Addnoise proc Additive Gausian noise adds a normal Gaussian curve with mean 0 and standard deviation specified by parameter, "sigma", to the input image. Regardless of the original image, because we are adding a normal Gaussian curve to the image, subtracting original image from the output should give us the Gaussian curve with mean 0 and standard diviation sigma back. In this case, adding a positive constant value such that the mean is shifted to 128 from 0, but standard deviation stays the same. www-mipl.jpl.nasa.gov /it/cookbook/adnoi.html   (276 words)

 Fast EM-algorithm by Filtering of Gaussian Noise is mostly due to the other sources and to a small extent the Gaussian noise in the data. By the central limit theorem, the distribution of the sum of contributions from several other sources approaches Gaussian as the number of other sources increases. is the projection of Gaussian noise to the subspace spanned by a and therefore represents the contribution of the other sources and some Gaussian noise to the estimated source www.cis.hut.fi /harri/ica2000a/node3.html   (468 words)

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