Gaussian random white noise is one of the mostly used signal form and is widely used in digital signal processing and analysis.
高斯随机白噪声是一种常用的信号形式，在信号分析和信号处理中具有重要价值。
Finally, the law that random Gaussian white noise influencing synthesized images is found through simulation examples based on the noise influence evaluation function.
最后，以该函数为基础，通过计算机仿真实验，找到了合成图像受随机高斯白噪声影响的规律。
The paper proposes a new method of adaptive smooth filter, based on that to design a Gaussian kernel adaptive smooth filter so as to suppress the random noise spread on the infrared image.
文章提出了一种新的自适应平滑滤波方法，并据此设计自适应高斯核平滑滤波来抑制红外图像中的随机噪声。
White noise tending to Gaussian distribution is implemented by summing uniformly distributed random numbers according to the central limit theorem.
依据中心极限定理，用均匀分布随机数求和的方法得到趋于高斯分布的白噪声。
Therefore, least absolute deviation, which is more robust than least squares especially for Gaussian noise, is selected to reduce the random error.
绝对偏差最小法是一种适合于存在离群点时的稳健估计算法，可以克服最小二乘法仅在误差为正态分布时才有效的缺点。
Therefore, least absolute deviation, which is more robust than least squares especially for Gaussian noise, is selected to reduce the random error.
绝对偏差最小法是一种适合于存在离群点时的稳健估计算法，可以克服最小二乘法仅在误差为正态分布时才有效的缺点。
应用推荐