Gaussian distribution with random variablex, and its meanμand varianceσ2: N(x|μ,σ2)=1(2πσ2)1/2exp{−(x−μ)22σ2} Proof that Gaussian distribution is normalized: ∫−∞∞N(x|μ,σ2)dx=1 SupposeI=∫−∞∞exp(−x22σ2)dx ...
从理论的角度看,根据GP的定义,连续输入空间(时间或者是空间)中每个点都是与一个高斯分布的随机变量相关联,换言之就是,在任意一个时间或者空间点上,对应的随机变量都是满足高斯分布,而这个被满足的高斯分布的里面的决定量(mean和variance)又是被对应的高斯过程的中的mean function和covariance function所确定的。 因...
是均值(mean), 是方差(variance),方差的平方根 叫做标准误(standard deviation),方差的倒数 叫做精度(precision)。 高斯分布满足: 高斯分布是归一化的(如下图(左)所示): 变量 在高斯分布下的期望: 证明上式:令 ,则 式中第一项是奇函数,且在 内积分,所以为0;第二项积分部分为1,所以第二项为 ,即 。 表...
The equation describing the Gaussian distribution is (9-9)P(x ; m, σ)=(1/2πσ2)e−(x−m)2/2σ2 where m and σ2 are again the mean and variance. Equation 9-9 describes a symmetrical “bell-shaped” curve. As shown by Figure 9-1, the Gaussian distribution for m ...
μ,被叫做均值(mean),以及σ2,被叫做方差(variance)。方差的平方 根,由σ给定,被叫做标准(standard deviation)。方差的倒数,记作β = 1 ,被叫做精度。 分布的最大值是众数。对于正态分布来说,众数是等于均值的。 我们也对D维向量x的正态分布感兴趣(不包括我),它是这么定义的: ...
Noun1.Gaussian distribution- a theoretical distribution with finite mean and variance normal distribution distribution,statistical distribution- (statistics) an arrangement of values of a variable showing their observed or theoretical frequency of occurrence ...
aassumed to be independent over time and follow a Gaussian distribution with mean 0 and variance Σ(see Chapter 5 or Appendix 15.1 for a definition). 随着时间的过去假设是独立的和跟随高斯发行以手段0和变化Σ(为定义看第5章或附录15.1)。[translate]...
The noise in this paper the probability density function known zero mean, Gaussian distribution and variance estimated by the median absolute deviation of donoho obtained by fitting the probability density function of the signal ggd 翻译结果2复制译文编辑译文朗读译文返回顶部 正在翻译,请等待... 翻译结果...
• Cumulative distribution function Φ(z) = P(Z ≤ z) = z −∞ p(z )dz • Expectation E[g(X)] = g(x)p(x)dx • mean, E[X] • Variance E[(X −µ) 2 ] • For a Gaussian, mean = µ, variance =σ 2 • Shorthand: x ∼ N(µ, σ 2 ) Bivariate Ga...
The first and second moments of the distribution function of the arc length of a Gaussian process on a finite interval are obtained in terms of the covariance function of the derivative process. A closed expression (in terms of a modified Bessel function) was obtained for the first moment; ...