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