followed by the theoretical error rates of various modulations over theadditive white Gaussian noise (AWGN) channel. Finally, the complex baseband models for digital modulators and detectors developed inprevious
本文简要介绍python语言中 sklearn.gaussian_process.kernels.WhiteKernel 的用法。 用法: class sklearn.gaussian_process.kernels.WhiteKernel(noise_level=1.0, noise_level_bounds=(1e-05, 100000.0))白仁。该内核的主要用例是作为sum-kernel 的一部分,它以独立且相同的方式解释信号的噪声normally-distributed。参数...
这次介绍一个很酷的idea，aka 高斯过程回归（Gaussian Process Regression)。
这里的阈值自适应确定,(model the objective function as a Gaussian process) 2)Partitioning 切分 Model Compression and Acceleration Overview ; Post-training量化策略:针对预训练模型,通过适当调整kernel参数分布、或补偿量化误差,可有效提升量化效果; 关于量化的比较系统性的论述:Quantizing deep convolutional ...
3. Images were then smoothed with a 1 mm full-width half-maximum Gaussian kernel. The resulting residual images were used as inputs for the partial least squares (PLS) analysis (see below). APOE4 genotyping Methods for participant genotyping have been described previously79. Briefly, DNA ...
[63], the following steps were applied to obtain estimates of the RS oscillatory peaks and the aperiodic offset and exponent measures. First, an initial aperiodic fit was applied to the power spectrum and removed, with the residual activity fitted with a Gaussian function (using the above spec...
mid-thickness surfaces between the cortical pial surface and white matter surface provided by Freesurfer segmentation were computed using the wb_command -surface-cortex-layer function provided by Workbench command. A Gaussian smoothing kernel (FWHM = ~4 mm, σ = 5/3 mm) was applied...
The uncertainty of each pKa value was determined by randomly varying the observed ΔΔG°fold values using a Gaussian distribution (mean 0 kJ/mol, standard deviation by 1 kJ/mol) and refitting to Eq. 7. In addition to varying the experimental energies in this way, the starting values of ...
To reduce the effect of fine-grained local variations in anatomy between participants, data was smoothed by combining the signal from neighbouring voxels applying a 4-mm full width at half maximum (FWHM) Gaussian smoothing. Advanced Normalization Tools (ANTs) (Avants et al., 2009) was used to...
Image pre-processing:In this step, Gaussian filter using a window of size (5 × 5) was applied to remove the random noise in the image. The image was converted after that to LAB color space. The L*a*b color space comprises of three different layers namely luminosity layer ‘L*’...