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Noisy speech is processed by the noise suppression algorithm and the noise-suppressed signal is input to the G.711, G.729 or AMR speech codec.
Specifically, in the unified frequency domain architecture, the acoustic echo and noise signal are efficiently able to be suppressed through the acoustic echo suppression algorithm based on soft decision without the help of the additional noise reduction technique.
For example, for the geographic PUMF using PROV_ALL at the 0.04 threshold with the complete suppression algorithm results in 13.6% of the cells being suppressed, whereas our recommended PUMF has only 8.4% of its cells suppressed.
In this paper we propose a novel impulse noise suppression algorithm for infrared images based on fuzzy logic.
In this paper, a regression-based integrated acoustic echo and background noise suppression algorithm was proposed through the use of a deep neural network (DNN) with a multi-layer deep architecture.
To improve the detection performance for non-morphological multi-scale target in IR image containing complex cloud clutter, on basis of cloud scenario self-similarity feature, a non-local and nonlinear background suppression algorithm controlled by multi-scale clutter metric is presented.
Similar(16)
In these experiments, some sidelobe suppression algorithms are used.
The ED method and the Notch filtering method are still as contrast RFI suppression algorithms.
To minimise metal artefacts in both CBCT and MSCT, artefact suppression algorithms are used and will be further developed [24].
Two MMSE-based interference suppression algorithms are implemented according to the analysis and design presented in Section 6.
In [9], effective sidelobe suppression algorithms were introduced for discrete point targets and contiguous scattering targets, which we refer to as the CLEAN algorithm in this paper.
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