最小均方差估计
最小均方差估计(Minimum mean-square error(缩写MMSE))是一种使均方差最小的估计函数,其通常被称为最优估计。
- Johnson, D. (2004, November 22). Minimum Mean Squared Error Estimators. Connexions
单词 | Minimum mean square error |
释义 |
Minimum mean square error
中文百科
最小均方差估计最小均方差估计(Minimum mean-square error(缩写MMSE))是一种使均方差最小的估计函数,其通常被称为最优估计。
英语百科
Minimum mean square error 最小均方差估计In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE), which is a common measure of estimator quality, of the fitted values of a dependent variable. In the Bayesian setting, the term MMSE more specifically refers to estimation with quadratic cost function. In such case, the MMSE estimator is given by the posterior mean of the parameter to be estimated. Since the posterior mean is cumbersome to calculate, the form of the MMSE estimator is usually constrained to be within a certain class of functions. Linear MMSE estimators are a popular choice since they are easy to use, calculate, and very versatile. It has given rise to many popular estimators such as the Wiener-Kolmogorov filter and Kalman filter. |
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