Function: norml2
Section: conversions
C-Name: gnorml2
Prototype: G
Help: norml2(x): square of the L2-norm of the vector x.
Doc:
 square of the $L^2$-norm of $x$. More precisely,
 if $x$ is a scalar, $\kbd{norml2}(x)$ is defined to be \kbd{$x$ * conj($x$)}.
 If $x$ is a polynomial, a (row or column) vector or a matrix, \kbd{norml2($x$)} is
 defined recursively as $\sum_i \kbd{norml2}(x_i)$, where $(x_i)$ run through
 the components of $x$. In particular, this yields the usual $\sum |x_i|^2$
 (resp.~$\sum |x_{i,j}|^2$) if $x$ is a polynomial or vector (resp.~matrix) with
 complex components.

 \bprog
 ? norml2( [ 1, 2, 3 ] )      \\ vector
 %1 = 14
 ? norml2( [ 1, 2; 3, 4] )   \\ matrix
 %2 = 30
 ? norml2( 2*I + x )
 %3 = 5
 ? norml2( [ [1,2], [3,4], 5, 6 ] )   \\ recursively defined
 %4 = 91
 @eprog
