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norm    See Also

Vector and matrix norms

Syntax

Description

The norm of a matrix is a scalar that gives some measure of the magnitude of the elements of the matrix. The norm function calculates several different types of matrix norms:

n = norm(A) returns the largest singular value of A, max(svd(A)).

n = norm(A,p) returns a different kind of norm, depending on the value of p:

If p is...
Then norm returns...
1
The 1-norm, or largest column sum of A, max(sum(abs((A))).
2
The largest singular value (same as norm(A)).
inf
The infinity norm, or largest row sum of A, max(sum(abs(A'))).
'fro'
The Frobenius-norm of matrix A, sqrt(sum(diag(A'*A))).

When A is a vector, slightly different rules apply:

norm(A,p)
Returns sum(abs(A).^p)^(1/p), for any .
norm(A)
Returns norm(A,2).
norm(A,inf)
Returns max(abs(A)).
norm(A,-inf)
Returns min(abs(A)).

Remarks

To obtain the root-mean-square (RMS) value, use norm(A)/sqrt(n). Note that norm(A), where A is an n-element vector, is the length of A.

See Also

cond        Condition number with respect to inversion

normest     2-norm estimate

svd         Singular value decomposition



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