Traffine I/O

Bahasa Indonesia

2022-12-16

Ekspresi matematika di LaTeX

Apa itu LaTeX

LaTeX adalah bahasa markup yang dapat dengan indah menghasilkan dokumen yang berisi struktur kompleks seperti ekspresi matematika, dan sering digunakan dalam bidang ilmiah seperti matematika dan fisika. Ekspresi matematika dapat direpresentasikan dalam teks LaTeX dengan menyisipkan string di antara simbol $ dan $.

Ekspresi matematika di LaTeX

Ekspresi matematis LaTeX
\equiv $\equiv$
\approx $\approx$
\fallingdotseq $\fallingdotseq$
\risingdotseq $\risingdotseq$
\sim $\simeq
\geq $\geq
\geqq $\geqq
\leq $\leq
\leqq $\leqq
\gg $\gg
\ll $\ll
\N $\N
\Z $\Z
\R $\R
\exist $\exist
\forall $\forall
\times $\times
\ast $\ast
\div $\div
\pm $\pm
\mp $\mp
\oplus $\oplus
\ominus $\ominus
\otimes $\otimes
\oslash $\oslash
\circ $\circ
\ltimes $\ltimes
\rtimes $\rtimes
\in $\in
\ni $\ni
\notin $\notin
\subset $\subset
\supset $\supset
\subseteq $\subseteq
\supseteq $\supseteq
\nsubseteq $\nsubseteq
\nsupseteq $\nsupseteq
\cap $\cap
\cup $\cup
\emptyset $\emptyset
\varnothing $\varnothing
\parallel $\parallel
x^2 $x^2$
x^{10} $x^{10}$
x^{y+1} $x^{y+1}$
x_i $x_i$
x_i^2 $x_i^2$
_n C _r $_n C _r$
\mathrm{e}^x $\mathrm{e}^x$
\pi $\pi$
\alpha $\alpha$
\beta $\beta$
\gamma $\gamma$
\mu $\mu$
\nu $\nu$
\theta $\theta$
\eta $\eta$
\delta $\delta$
\zeta $\zeta$
\ell $\ell$
\epsilon $\epsilon$
\sigma $\sigma$
\lambda $\lambda$
\tau $\tau$
\omega $\omega$
\phi $\phi$
\chi $\chi$
\nabla $\nabla$
\psi $\psi$
\kappa $\kappa$
\xi $\xi$
\varepsilon $\varepsilon$
\vartheta $\vartheta$
\varpi $\varpi$
\varsigma $\varsigma$
\varphi $\varphi$
\Gamma $\Gamma$
\Delta $\Delta$
\Omega $\Omega$
\to $\to$
\rightarrow $\rightarrow$
\Rightarrow $\Rightarrow$
\leftarrow $\leftarrow$
\Leftarrow $\Leftarrow$
\leftrightarrow $\leftrightarrow$
\Leftrightarrow $\Leftrightarrow$
\models $\models$
\cdots $\cdots$
\sin(x) $\sin(x)$
\cos(x) $\cos(x)$
\tan(x) $\tan(x)$
\neq $\neq$
x_1, x_2, \cdots, x_n $x_1, x_2, \cdots, x_n$
\dot{x} $\dot{x}$
\ddot{x} $\ddot{x}$
\vec{x} $\vec{x}$
\hat{x} $\hat{x}$
\bar{x} $\bar{x}$
\tilde{x} $\tilde{x}$
\overrightarrow{x} $\overrightarrow{x}$
\overleftarrow{x} $\overleftarrow{x}$
\infty $\infty$
\int $\int$
\lim $\lim$
\lim_{n\to \infty} a_n $\lim_{n\to \infty} a_n$
\mathrm{d} x $\mathrm{d} x$
F(x)=\int f(x) \mathrm{d} x $F(x) = \int f(x) \mathrm{d} x$
\sqrt{x} $\sqrt{x}$
\sqrt[n]{a} $\sqrt[n]{a}$
\int_{-\infty}^{\infty} \mathrm{e}^{-x^2} \mathrm{d} x $\int_{-\infty}^{\infty} \mathrm{e}^{-x^2} \mathrm{d} x$
\sum $\sum$
\sum_i^N x_i $\sum_i^N x_i$
\prod $\prod$
\prod_i x_i $\prod_i x_i$
\frac{1}{2} $\frac{1}{2}$
\sum_{k=0}^\infty \frac{h^k f^{k}(x)}{k!} $\sum_{k=0}^\infty \frac{h^k f^{k}(x)}{k!}$
a \mathrm{a} $a \mathrm{a}$
\left( \right) $\left \right)$
\left( \frac{x}{y} \right) $\left( \frac{x}{y} \right)$
\left[ \frac{x}{y} \right] $\left[ \frac{x}{y} \right]$
\left( \frac{x}{y} \right. $\left( \frac{x}{y} \right.$
\partial $\partial$
\frac{\partial f}{\partial x} $\frac{\partial f}{\partial x}$
\\ $\\$
\quad $\quad$
\underset{k}{\textrm{argmax}} $\underset{k}{\textrm{argmax}}$
\textrm{precision} × \textrm{recall} $\textrm{precision} × \textrm{recall}$

Diferensial

\left. \frac{dy}{dx} \right|_{x=1}
$$
\left. \frac{dy}{dx} \right|_{x=1}
$$

Persamaan Multiline

\begin{aligned} (x+y)^2 &= (x+y) (x+y) \\ &= x(x+y) + y (x+y) \\ &= x^2 + xy + yx + y^2 \\ &= x^2 + 2xy+y^2 \end{aligned}
$$
\begin{aligned}
  (x+y)^2 &= (x+y) (x+y) \\
  &= x(x+y) + y (x+y) \\
  &= x^2 + xy + yx + y^2 \\
  &= x^2 + 2xy+y^2
\end{aligned}
$$

Matriks

\begin{pmatrix} a & b\\ c & d \end{pmatrix}
$$
\begin{pmatrix}
  a & b\\
  c & d
\end{pmatrix}
$$
\begin{bmatrix} a & b\\ c & d \end{bmatrix}
\begin{bmatrix}
a & b\\
c & d
\end{bmatrix}
\begin{Vmatrix} a & b \\ c & d \end{Vmatrix}
$$
\begin{Vmatrix}
  a & b \\
  c & d
\end{Vmatrix}
$$
\left( \begin{array}{c} (x^{1})^T\\ \vdots\\ (x^{N})^T\\ \end{array} \right)
$$
\left(
  \begin{array}{c}
    (x^{1})^T\\
    \vdots\\
    (x^{N})^T\\
  \end{array}
\right)
$$
A = \left( \begin{array}{ccccc} 1 & 1 & 4 & 5 & 1 \\ 1 & 0 & 5 & 0 & 4 \\ 4 & 5 & 1 & 4 & 0 \end{array} \right)
$$
A = \left(
  \begin{array}{ccccc}
    1 & 1 & 4 & 5 & 1 \\
    1 & 0 & 5 & 0 & 4 \\
    4 & 5 & 1 & 4 & 0
  \end{array}
\right)
$$
\begin{pmatrix} a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\ \vdots & \ddots & & & \vdots \\ a_{i1} & & a_{ii} & & a_{in} \\ \vdots & & & \ddots & \vdots \\ a_{n1} & \cdots & a_{ni} & \cdots & a_{nn} \end{pmatrix} \times \begin{vmatrix} a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\ \vdots & \ddots & & & \vdots \\ a_{i1} & & a_{ii} & & a_{in} \\ \vdots & & & \ddots & \vdots \\ a_{n1} & \cdots & a_{ni} & \cdots & a_{nn} \end{vmatrix}
$$
\begin{pmatrix}
  a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\
  \vdots & \ddots &        &        & \vdots \\
  a_{i1} &        & a_{ii} &        & a_{in} \\
  \vdots &        &        & \ddots & \vdots \\
  a_{n1} & \cdots & a_{ni} & \cdots & a_{nn}
\end{pmatrix}

\times

\begin{vmatrix}
  a_{11} & \cdots & a_{1i} & \cdots & a_{1n}\\
  \vdots & \ddots &        &        & \vdots \\
  a_{i1} &        & a_{ii} &        & a_{in} \\
  \vdots &        &        & \ddots & \vdots \\
  a_{n1} & \cdots & a_{ni} & \cdots & a_{nn}
\end{vmatrix}
$$

Conditional Branch

f(x) = \left\{ \begin{array}{ll} 1 & (x = 1) \\ 0 & (otherwise) \end{array} \right.
$$
f(x) = \left\{
  \begin{array}{ll}
    1 & (x = 1) \\
    0 & (otherwise)
  \end{array}
\right.
$$

Nomor Persamaan

\tag{1.0.2} x_i = \sigma (W_i + \beta)
$$
\tag{1.0.2}
x_i = \sigma (W_i + \beta)
$$

Pemrograman Linier

\begin{equation*} \begin{aligned} & \text{minimize} & {\bf c}^T{\bf x} \\ & \text{s.t.} & A{\bf x} \le {\bf b} \\ & & {\bf x} \ge {\bf 0} \\ \end{aligned} \end{equation*}
$$
\begin{equation*}
  \begin{aligned}
    & \text{minimize}
      & {\bf c}^T{\bf x} \\
    & \text{s.t.}
      & A{\bf x} \le {\bf b} \\
      & & {\bf x} \ge {\bf 0} \\
  \end{aligned}
\end{equation*}
$$

Metode Simpleks

\begin{array}{rrrrrrr} x_3 & = & 1 & + & x_1 & - & x_2 \\ x_4 & = & 3 & - & x_1 & & \\ x_5 & = & 2 & & & - & x_2 \\ \hline z & = & & & x_1 & + & x_2 \end{array}
$$
\begin{array}{rrrrrrr}
  x_3 & = & 1 & + & x_1 & - & x_2 \\
  x_4 & = & 3 & - & x_1 &   &     \\
  x_5 & = & 2 &   &     & - & x_2 \\ \hline
  z   & = &   &   & x_1 & + & x_2
\end{array}
$$

Ryusei Kakujo

researchgatelinkedingithub

Weave the future of cities through data

Transportation modeling/ Urban planning/ Machine learning/ Computer science/ GIS