approximate derivative

基本解釋

With the aid of the approximate second derivative, the LM algorithm is more efficient than the gradient method.
由于利用了近似的二階導(dǎo)數(shù)信息，LM算法比梯度法快得多。
The results of classical cases indicate that the sensitivity derivative gained by approximate method has good accuracy and the inverse design can be completed efficiently with reduced total CPU time.
典型的算例結(jié)果表明簡化方法計算得到的敏感性導(dǎo)數(shù)具較高的精度，能夠有效完成反問題設(shè)計且減少總的計算耗時。
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Because of the finite sample size, the precise limit and derivative does not exist. However, the approximate derivative will provide insight into the game balance.
因為樣本大小有限，精確極限和導(dǎo)數(shù)不存在，最近似的導(dǎo)數(shù)可以洞悉游戲平衡性。
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