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White Gaussian Noise (WGN) is a statistical noise characterized by a flat spectral density across a range of frequencies and follows a Gaussian distribution. This means that its amplitudes are normally distributed, with a mean of zero and a certain variance. WGN is often used in signal processing and telecommunications as a model for random noise, providing a baseline for analyzing and designing systems that operate in noisy environments. Its "white" aspect refers to the equal intensity of its frequencies, akin to how white light contains all visible colors.
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What is the difference between white Gaussian noise and additive white Gaussian noise?
A Gaussian noise is a type of statistical noise in which the amplitude of the noise follows that of a Gaussian distribustion whereas additive white Gaussian noise is a linear combination of a Gaussian noise and a white noise (white noise has a flat or constant power spectral density).
What is the difference between white noise and gaussian noise?
White noise is a type of signal that has a flat power spectral density across all frequencies, meaning that all frequencies have equal power. Gaussian noise refers to noise with a normal distribution in the time domain. While white noise has uniform power across all frequencies, Gaussian noise has a distribution of values that follows the Gaussian (bell-shaped) curve.
What is AWGN channel?
An AWGN channel adds white Gaussian noise to the signal that passes through it.
What is circular complex Additive White Gaussian Noise?
"Circular" means the variance of the real and imaginary parts are equal. "White" refers to the fact that the power spectral density of the noise is flat across the whole frequency spectrum. This means that its autocorrelation is a Dirac-delta at t=0 (so its covariance matrix will show noise powers on the diagonal elements and zeros elsewhere). "Gaussian" means the probability distribution of the amplitudes of the noise samples is Gaussian.
What do you mean by Gaussian noise?
Gaussian noise is similar to white noise, but it falls within a narrower range of frequencies. In communications, it is produced by the movement of electricity through the line. You see and hear that when you have your television on an empty channel. Within photos and videos, Gaussian noise is in the form of random patterns, and this is what makes things look slightly blurry.
A communication channel with additive white gaussian noise has a bandwidth of 4kHz and SNR of 31dB. Its channel capacity is?
20kbps
What do you mean by gaussian?
The Gaussian distribution is the same as the normal distribution. Sometimes, "Gaussian" is used as in "Gaussian noise" and "Gaussian process." See related links, Interesting that Gauss did not first derive this distribution. That honor goes to de Moivre in 1773.
Why thermal noise is called white noise?
Thermal noise occurs due to the motion of millions of electrons in a object. Due to the central limit theorem, the total effect can be modeled as a Gaussian distributed random variable with zero mean and N_0/2 variance.
What has the author Takeyuki Hida written?
Takeyuki Hida has written: 'Complex white noise and infinite dimensional unitary group' -- subject(s): Gaussian processes, Linear algebraic groups, Unitary groups, Wiener integrals 'Mathematical Approach to Fluctuations: Astronomy, Biology and Quantum Dynamics : Proceedings of the Iias Workshop' 'Complex white noise and infinite dimensional untrary group' -- subject(s): Gaussian processes, Random noise theory, Stochastic processes 'Stationary stochastic processes' -- subject(s): Stationary processes
What has the author G Kallianpur written?
G. Kallianpur has written: 'White noise theory of prediction, filtering, and smoothing' -- subject(s): Gaussian processes, Kalman filtering, Prediction theory
Is salt and pepper noise an impulse noise?
Yes, salt and pepper noise is a type of impulse noise. It manifests as random bright (white) and dark (black) pixels in an image, resembling grains of salt and pepper. This noise occurs due to sudden disturbances in the signal, often resulting from transmission errors or sensor faults. It is characterized by its sporadic nature, differentiating it from other types of noise like Gaussian noise.
What has the author Percy A Pierre written?
Percy A. Pierre has written: 'Characterizations of Gaussian random processes by representations in terms of independent random variables' -- subject(s): Gaussian processes, Random noise theory
