1) sub-and super-Gaussian
亚、超高斯
1.
An algorithm for blind separation of post-nonlinearly mixed sub- and super-Gaussian signals based on the results of previous work is proposed.
研究后非线性混合信号的盲分离 ,从最大似然角度推导了一般后非线性分离结构的学习公式 ;在前人一些工作的基础上 ,提出一种用于亚、超高斯信号后非线性混合的盲分离算法 。
2) super Gaussian and sub Gaussian
超高斯和亚高斯
3) sub-Gaussian
亚高斯
1.
The performance of existing blind source separation methods is highly affected by the non-linear contrast functions that are selected according to the distribution of original signals, and the separation results are not always ideal, especially for the mixture of super-Gaussian signal and sub-Gaussian signal.
对模拟信号的分离结果表明,该算法可以成功地分离混叠信号,同时与快速独立分量分析算法相比,该算法的性能对源信号的概率密度性质没有依赖,因而对亚高斯和超高斯信号的混合信号表现出更加优异的分离能力。
2.
In this paper,sub-Gaussian random projection is introduced into compressed sensing(CS) theory and two new kinds of CS measurement matrix:sparse projection matrix and very sparse projection matrix are presented.
将亚高斯随机投影引入可压缩传感CS(compressed sensing)理论,给出了两种新类型的CS测量矩阵:稀疏投影矩阵和非常稀疏投影矩阵。
3.
In order to separate super-Gaussian and sub-Gaussian signals,this paper uses high-and low-frequency coefficients of wavelet transform as smooth factors,then builds a signal-to-noise ratio objective function,which uses the denominator as prediction error and can be optimized to resolve separable matrix.
为了分离超高斯与亚高斯信号,利用小波变换的高低频系数作为平滑因子,建立以分母作为预测误差的信噪比目标函数,优化目标函数以求解分离矩阵。
4) super-Gaussian
超高斯
1.
Study on the generation of super-Gaussian and true-random drive signals using time domain randomization;
基于时域随机化的超高斯真随机驱动信号生成技术研究
2.
The technique of generating super-Gaussian and quasi-random vibration exciting signals;
超高斯伪随机振动激励信号的生成技术
3.
The performance of existing blind source separation methods is highly affected by the non-linear contrast functions that are selected according to the distribution of original signals, and the separation results are not always ideal, especially for the mixture of super-Gaussian signal and sub-Gaussian signal.
对模拟信号的分离结果表明,该算法可以成功地分离混叠信号,同时与快速独立分量分析算法相比,该算法的性能对源信号的概率密度性质没有依赖,因而对亚高斯和超高斯信号的混合信号表现出更加优异的分离能力。
5) super-Gaussian mirror
超高斯镜
6) meta-gaussian model
亚高斯模型
1.
A meta-gaussian model is developed, at the heart of which is the normal quantile transform.
根据贝叶斯分析,用先验分布考虑水文要素的自然不确定性,用似然函数描述水文模型和参数的不确定性,通过亚高斯模型对实际流量与模拟流量进行正态分位数转化,并对转化后的时间序列进行线性-正态假设,得到实际流量的后验密度函数的解析解。
2.
Then both the initial predicted discharge series and the corresponding observations are normalized by Meta-Gaussian model.
以新安江流域水文模型为洪水预报模型提供流量初始预报系列,通过亚高斯模型对流量初始预报系列及实测系列分别进行正态分位数变换,由贝叶斯公式得到预报变量的后验概率分布并进行洪水过程的概率预报,采用分布点估值定值预报,并可通过构造置信区间对点估值预报的不确定性进行评估。
补充资料：超超
1.谓超然出尘。 2.高高在上貌。 3.犹绰绰。 4.见"超超玄箸"。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条