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A noise gate or simply gate is an electronic device or software that is used to control the volume of an audio signal. Comparable to a compressor, which attenuates signals above a threshold, such as loud attacks from the start of musical notes, noise gates attenuate signals that register below the threshold. [1]
Frequency-resolved optical gating. Frequency-resolved optical gating (FROG) is a general method for measuring the spectral phase of ultrashort laser pulses, which range from sub femtosecond to about a nanosecond in length. Invented in 1991 by Rick Trebino and Daniel J. Kane, FROG was the first technique to solve this problem, which is difficult ...
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 ...
Gating signal. Signal gating is a concept commonly used in the field of electronics and signal processing. It refers to the process of controlling the flow of signals based on certain conditions or criteria. The goal of signal gating is to selectively allow or block the transmission of signals through a circuit or system.
Block-matching and 3D filtering (BM3D) is a 3-D block-matching algorithm used primarily for noise reduction in images. [1] It is one of the expansions of the non-local means methodology. [2] There are two cascades in BM3D: a hard-thresholding and a Wiener filter stage, both involving the following parts: grouping, collaborative filtering, and ...
Spyder is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language. Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software. [ 4 ][ 5 ] It is ...
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]
Glitch removal is the elimination of glitches —unnecessary signal transitions without functionality—from electronic circuits. Power dissipation of a gate occurs in two ways: static power dissipation and dynamic power dissipation. Glitch power comes under dynamic dissipation in the circuit and is directly proportional to switching activity.