混合高斯模型(MoG)的参数估计方法一般是期望最大化(Expectation Maximization)算法,期望最大化算法(简称EM算法)主要根据特定分布中可能 包含信息丢失的样本来估计样本所服从的分布的参数,其核心思想就是根...
基于142个网页-相关网页
关键词 :多输入输出;正交频分复用;信道估计;期望最大化;误差地板 [gap=1342]Key words: MIMO; OFDM; channel estimation; EM; error floor
基于22个网页-相关网页
We resort to expectation maximization (EM) algorithm for both the estimation of model parameters and the coping with missing values.
这里,期望最大化算法既用来处理丢失值又用来估计模型参数。
参考来源 - 有限混合模型、非线性二维主成分分析及其在模式分类中应用·2,447,543篇论文数据,部分数据来源于NoteExpress
隐马尔可夫模型参数通过期望最大化算法(EM)来估计。
这里,期望最大化算法既用来处理丢失值又用来估计模型参数。
We resort to expectation maximization (EM) algorithm for both the estimation of model parameters and the coping with missing values.
该算法采用期望最大化(EM)聚类分析方法来识别分类及其顺序。
The algorithm USES the Expectation Maximization (EM) clustering method to identify clusters and their sequences.
What finance theory is based on-- and much of economics is based on-- the idea that people want to maximize the expected utility of their wealth.
金融学理论建立在,并且很多经济学的都是建立在,人们希望能使自己对,财富的期望效用最大化这一基础上
Of course, we will also be talking about behavioral finance in this course and we'll, at times, be saying that the utility function concept isn't always right-- the idea that people are actually maximizing expected utility might not be entirely accurate.
当然 我们还会,在这门课上讨论行为金融学,并且,我们会间或,讨论到效用函数不总是正确的,人们希望最大化期望效用的观点,也许并不是完全准确的
应用推荐