偏微商

强震前重力场等位面二次偏微商异常变化分析

Analysis of the anomalous change of quadratic partial derivative of gravity equi-potential surface prior to strong earthquakes

我们可用普通微商代替偏微商。

We will replace the partial derivative by an ordinary derivative .

热力学函数偏微商推证法的探讨

Study on the deducing methods of the partial derivatives in thermodynamic function

推证热力学函数偏微商的简捷方法

A Simplified Method of Deducing partial Derivatives of Thermodynamic Function

偏微商求值十分简单。

The evaluation of partial derivation is quite simple .

化学热力学函数偏微商等式证明方法探讨

Discussion on the Deduction Methods for the Partial Differential Equations of Chemical Thermodynamics Functions

热力学偏微商的直接推证法

The Direct Conversion Method of Thermodynamic Partial Derivatives

偏微商的次序并不重要。

The order of partial differentiation is immaterial .

介绍了基于热力学偏微商关系的变量变换方法，讨论了在物理化学教学中的必要性及基本要求。

This article describes the variable transformation method for the partial differential relationship of thermodynamics and discusses the necessity and fundamental requests in physical chemistry teaching .

以法国数理学家拉普拉斯命名的这个方程式表述如下：一个未知函数的二级偏微商之和（拉普拉斯算符）等于零。

Named for Pierre-Simon Laplace , the equation states that the sum of the second partial derivatives ( the Laplace operator , or Laplacian ) of an unknown function is zero .

给出了左、右特征向量微商的解析表达式，进一步可得出它们的任何阶偏微商的表达式。

The analytic expressions of derivatives of both left and right eigenvectors have been showed , further , we can get any partial derivatives of higher order on the eigenvalues and the corresponding eigenvectors .

对热力学函数偏微商的推证方法进行了概述与探讨，找到了适合于教学的简单易记的推证法。

In this paper , the deducing methods of the partial derivatives in thermodynamic function Were summarized and studied , the author found simple and easily memorized method which could be applied well in the teaching .

采用数值微商求偏导数的方法，从而使GPS网平差的计算模型非常简洁。强震前重力场等位面二次偏微商异常变化分析

The numerical partial derivative is introduced to simplify the GPS network adjustment model . ANALYSIS OF THE ANOMALOUS CHANGE OF QUADRATIC PARTIAL DERIVATIVE OF GRAVITY EQUI-POTENTIAL SURFACE PRIOR TO STRONG EARTHQUAKES