LaTeX是一种基于ΤΕΧ的排版系统,通过输入特定的符号即可生成复杂的数学公式。你可以在网上查询和学习如何运用LaTeX来生成数据公式,以下一些例子可以作为参考。
Square of sums
(a_1 + a_2)^2 = a_1^2 + 2a_1a_2 + a_2^2
Quadratic Formula
x = \frac{-b \pm \sqrt{b^2-4ac}}{2a}
Standard Deviation
\sigma = \sqrt{\frac{1}{N}\sum_{i=1}^N (x_i - \mu)^2}
De Morgan's laws
\neg(P\land Q) \iff (\neg P)\lor(\neg Q)
Log Change of Base
\log_b(x) = \frac{\log_a(x)}{\log_a(b)}
Cosine addition
\cos(\theta + \varphi) = \cos(\theta)\cos(\varphi) - \sin(\theta)\sin(\varphi)
Limit e^k
\lim_{x\to\infty}\left(1 + \frac{k}{x}\right)^x = e^k
Calculus
f(x) = \int\limits_{-\infty}^\infty\!\hat f(\xi)\,e^{2 \pi i \xi x}\,\mathrm{d}\xi
Stirling Numbers of the Second Kind
{n \brace k} = \frac{1}{k!}\sum_{j=0}^k (-1)^{k-j}\binom{k}{j}(k-j)^n
Gaussian Integral
\int_{-\infty}^{\infty} \! e^{-x^2} dx = \sqrt{\pi}
Arithmetic mean, geometric mean inequality
\frac{1}{n}\sum_{i=1}^{n}x_i \geq \sqrt[n]{\prod_{i=1}^{n}x_i}
Cauchy-Schwarz inequality
\left(\sum_{k=1}^n a_k b_k \right)^2 \le \left(\sum_{k=1}^n a_k^2\right)\left(\sum_{k=1}^n b_k^2\right)
Cauchy integral formula
f^{(n)}(z_0) = \frac{n!}{2\pi i}\oint_\gamma\frac{f(z)}{(z-z_0)^{n+1}}dz
Schroedinger's Equation
i\hbar\frac{\partial}{\partial t}\mathbf\Psi(\mathbf{x},t) = -\frac{\hbar}{2m}\nabla^2\mathbf\Psi(\mathbf{x},t) + V(\mathbf{x})\mathbf\Psi(\mathbf{x},t)
Lorentz Equations
\begin{gather}
\dot{x} = \sigma(y-x) \\
\dot{y} = \rho x - y - xz \\
\dot{z} = -\beta z + xy
\end{gather}
Cross product
\vec \bf V_1 \times \vec \bf V_2 = \begin{vmatrix}
\hat \imath &\hat \jmath &\hat k \\
\frac{\partial X}{\partial u} & \frac{\partial Y}{\partial u} & 0 \\
\frac{\partial X}{\partial v} & \frac{\partial Y}{\partial v} & 0
\end{vmatrix}
Maxwell's Equations
\begin{eqalign}
\nabla \cdot \vec{\bf E} & = \frac {\rho} {\varepsilon_0} \\
\nabla \cdot \vec{\bf B} & = 0 \\
\nabla \times \vec{\bf E} &= - \frac{\partial\vec{\bf B}}{\partial t} \\
\nabla \times \vec{\bf B} & = \mu_0\vec{\bf J} + \mu_0\varepsilon_0 \frac{\partial\vec{\bf E}}{\partial t}
\end{eqalign}
Matrix multiplication
\begin{pmatrix}
a & b\\ c & d
\end{pmatrix}
\begin{pmatrix}
\alpha & \beta \\ \gamma & \delta
\end{pmatrix} =
\begin{pmatrix}
a\alpha + b\gamma & a\beta + b \delta \\
c\alpha + d\gamma & c\beta + d \delta
\end{pmatrix}
Cases
f(x) = \begin{cases}
\frac{e^x}{2} & x \geq 0 \\
1 & x < 0
\end{cases}
Splitting long equations
\frak Q(\lambda,\hat{\lambda}) =
-\frac{1}{2} \mathbb P(O \mid \lambda ) \sum_s \sum_m \sum_t \gamma_m^{(s)} (t) +\\
\quad \left( \log(2 \pi ) + \log \left| \cal C_m^{(s)} \right| +
\left( o_t - \hat{\mu}_m^{(s)} \right) ^T \cal C_m^{(s)-1} \right)