\begin{equation*}
\unionmany{k=1}{\infty}{A_{k}} = \intersectmany{k=1}{\infty}{B_{k}}
\end{equation*}
+
+ Finally, we have the four standard types of intervals in $\Rn[1]$,
+ %
+ \begin{align*}
+ \intervaloo{a}{b} &= \setc{ x \in \Rn[1]}{ a < x < b },\\
+ \intervaloc{a}{b} &= \setc{ x \in \Rn[1]}{ a < x \le b },\\
+ \intervalco{a}{b} &= \setc{ x \in \Rn[1]}{ a \le x < b }, \text{ and }\\
+ \intervalcc{a}{b} &= \setc{ x \in \Rn[1]}{ a \le x \le b }.
+ \end{align*}
+ \end{section}
+
+ \begin{section}{Complex}
+ We sometimes want to conjugate complex numbers like
+ $\compconj{a+bi} = a - bi$.
\end{section}
\begin{section}{Cone}
their tensor product is $\tp{x}{y}$. The Kronecker product of
matrices $A$ and $B$ is $\kp{A}{B}$. The adjoint of the operator
$L$ is $\adjoint{L}$, or if it's a matrix, then its transpose is
- $\transpose{L}$. Its trace is $\trace{L}$.
+ $\transpose{L}$. Its trace is $\trace{L}$. Another matrix-specific
+ concept is the Moore-Penrose pseudoinverse of $L$, denoted by
+ $\pseudoinverse{L}$.
The span of a set $X$ is $\spanof{X}$, and its codimension is
$\codim{X}$. The projection of $X$ onto $V$ is $\proj{V}{X}$. The