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Infinity Norm


The term infinity norm refers to two closely related norms. For a finite vector x=(x_1,...,x_n), the infinity norm, also called the maximum norm, is the L-norm

 ||x||_infty=max_(1<=i<=n)|x_i|.

More generally, the L-norm of an essentially bounded measurable function f is ||f||_infty=esssup_(x)|f(x)|, where the abbreviation esssup denotes the essential supremum. The finite-vector formula is the special case for a finite set with counting measure.

For a matrix, the infinity norm generally means the matrix norm induced by the vector infinity norm. It is the maximum absolute row sum norm,

 ||A||_infty=max_(1<=i<=m)sum_(j=1)^n|a_(ij)|.

In finite-dimensional spaces the vector infinity norm is equivalent to every vector norm, although their numerical values differ.


See also

Essential Supremum, L-Norm, Matrix Norm, Maximum Absolute Row Sum Norm, Vector Norm

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References

Horn, R. A. and Johnson, C. R. Matrix Analysis, 2nd ed. Cambridge, England: Cambridge University Press, 2013.Rudin, W. Real and Complex Analysis, 3rd ed. New York: McGraw-Hill, 1987.

Cite this as:

Weisstein, Eric W. "Infinity Norm." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/InfinityNorm.html

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