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A good example of time-controlled noise gating is the well-known "gated reverb" effect heard on the drums on the Phil Collins hit single "In the Air Tonight", created by engineer-producer Hugh Padgham, in which the powerful reverberation added to the drums is cut off by the noise gate after a few milliseconds, rather than being allowed to decay ...
In cryptography, pseudorandom noise (PRN[1]) is a signal similar to noise which satisfies one or more of the standard tests for statistical randomness. Although it seems to lack any definite pattern, pseudorandom noise consists of a deterministic sequence of pulses that will repeat itself after its period. [2]
Additive white Gaussian noise (AWGN) is a basic noise model used in information theory to mimic the effect of many random processes that occur in nature. The modifiers denote specific characteristics: Additive because it is added to any noise that might be intrinsic to the information system. White refers to the idea that it has uniform power ...
Perlin noise is a type of gradient noise developed by Ken Perlin in 1983. It has many uses, including but not limited to: procedurally generating terrain, applying pseudo-random changes to a variable, and assisting in the creation of image textures. It is most commonly implemented in two, three, or four dimensions, but can be defined for any ...
Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al. [1] The GRU is like a long short-term memory (LSTM) with a gating mechanism to input or forget certain features, [2] but lacks a context vector or output gate, resulting in fewer parameters than LSTM. [3]
Non-local means is an algorithm in image processing for image denoising. Unlike "local mean" filters, which take the mean value of a group of pixels surrounding a target pixel to smooth the image, non-local means filtering takes a mean of all pixels in the image, weighted by how similar these pixels are to the target pixel. This results in much ...
Deterministic noise. In (supervised) machine learning, specifically when learning from data, there are situations when the data values cannot be modeled. This may arise if there are random fluctuations or measurement errors in the data which are not modeled, and can be appropriately called stochastic noise; or, when the phenomenon being modeled ...
Noise print. A noise print is part of a technique used in noise reduction. A noise print is commonly used in audio mastering to help reduce the effects of unwanted noise from a piece of audio. In this case, the noise print would be a recording of the ambient noise in the room, which is then used in spectral subtraction to set multiple expanders ...