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A noise gate can be thought of as an extreme form of downward expansion as the noise gate make the quiet sounds (for instance: noise) quieter or even silent, depending on the floor setting. [2] Upward expansion makes the louder sounds above the threshold even louder.
An Alesis Micro Gate noise gate. 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]
Moving target indication (MTI) is a mode of operation of a radar to discriminate a target against the clutter. [1] It describes a variety of techniques used for finding moving objects, like an aircraft, and filter out unmoving ones, like hills or trees. It contrasts with the modern stationary target indication (STI) technique, which uses ...
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 ...
MUSIC method assumes that a signal vector, , consists of complex exponentials, whose frequencies are unknown, in the presence of Gaussian white noise, , as given by the linear model. n {\displaystyle \mathbf {x} =\mathbf {A} \mathbf {s} +\mathbf {n} .} is the amplitude vector. A crucial assumption is that number of sources,
The regularization parameter plays a critical role in the denoising process. When =, there is no smoothing and the result is the same as minimizing the sum of squares.As , however, the total variation term plays an increasingly strong role, which forces the result to have smaller total variation, at the expense of being less like the input (noisy) signal.
In mathematics, Wiener deconvolution is an application of the Wiener filter to the noise problems inherent in deconvolution. It works in the frequency domain, attempting to minimize the impact of deconvolved noise at frequencies which have a poor signal-to-noise ratio. The Wiener deconvolution method has widespread use in image deconvolution ...
Simplex noise is the result of an n -dimensional noise function comparable to Perlin noise ("classic" noise) but with fewer directional artifacts, in higher dimensions, and a lower computational overhead. Ken Perlin designed the algorithm in 2001 [1] to address the limitations of his classic noise function, especially in higher dimensions.