Section: Array Generation and Manipulations
norm function.  The general syntax is
y = norm(A,p)
where A is the matrix to analyze, and p is the
type norm to compute.  The following choices of p
are supported
p = 1 returns the 1-norm, or the max column sum of A
 p = 2 returns the 2-norm (largest singular value of A)
 p = inf returns the infinity norm, or the max row sum of A
 p = 'fro' returns the Frobenius-norm (vector Euclidean norm, or RMS value)
 1 <= p < inf returns sum(abs(A).^p)^(1/p)
 p unspecified returns norm(A,2)
 p = inf returns max(abs(A))
 p = -inf returns min(abs(A))
 
--> A = float(rand(3,4))
A = 
    0.0063    0.2224    0.7574    0.9848 
    0.7319    0.1965    0.7191    0.7010 
    0.8319    0.6392    0.8905    0.9280 
--> norm(A,1)
ans = 
    2.6138 
--> norm(A,2)
ans = 
    2.3403 
--> norm(A,inf)
ans = 
    3.2896 
--> norm(A,'fro')
ans = 
    2.4353 
Next, we calculate some vector norms.
--> A = float(rand(4,1))
A = 
    0.5011 
    0.3269 
    0.8192 
    0.7321 
--> norm(A,1)
ans = 
    2.3792 
--> norm(A,2)
ans = 
    1.2510 
--> norm(A,7)
ans = 
    0.8671 
--> norm(A,inf)
ans = 
    0.8192 
--> norm(A,-inf)
ans = 
    0.3269