Maple Professional
Maple Academic
Maple Student Edition
Maple Personal Edition
Maple Player
Maple Player for iPad
MapleSim Professional
MapleSim Academic
Maple T.A. - Testing & Assessment
Maple T.A. MAA Placement Test Suite
Möbius - Online Courseware
Machine Design / Industrial Automation
Aerospace
Vehicle Engineering
Robotics
Power Industries
System Simulation and Analysis
Model development for HIL
Plant Modeling for Control Design
Robotics/Motion Control/Mechatronics
Other Application Areas
Mathematics Education
Engineering Education
High Schools & Two-Year Colleges
Testing & Assessment
Students
Financial Modeling
Operations Research
High Performance Computing
Physics
Live Webinars
Recorded Webinars
Upcoming Events
MaplePrimes
Maplesoft Blog
Maplesoft Membership
Maple Ambassador Program
MapleCloud
Technical Whitepapers
E-Mail Newsletters
Maple Books
Math Matters
Application Center
MapleSim Model Gallery
User Case Studies
Exploring Engineering Fundamentals
Teaching Concepts with Maple
Maplesoft Welcome Center
Teacher Resource Center
Student Help Center
linalg[norm] - norm of a matrix or vector
Calling Sequence
norm(A)
norm(A, normname)
Parameters
A
-
matrix or vector
normname
(optional) matrix/vector norm
Description
Important: The linalg package has been deprecated. Use the superseding packages, LinearAlgebra and VectorCalculus, instead.
- For information on migrating linalg code to the new packages, see examples/LinearAlgebraMigration.
The function norm(A, normname) computes the specified matrix or vector norm for the matrix or vector A.
For matrices, normname should be one of: 1, 2, 'infinity', 'frobenius'.
For vectors, normname should be one of: any real constants >=1, 'infinity', 'frobenius'.
The default norm used throughout the linalg package is the infinity norm. Thus norm(A) computes the infinity norm of A and is equivalent to norm(A, infinity).
For vectors, the infinity norm is the maximum magnitude of all elements. The infinity norm of a matrix is the maximum row sum, where the row sum is the sum of the magnitudes of the elements in a given row.
The frobenius norm of a matrix or vector is defined to be the square root of the sum of the squares of the magnitudes of each element.
The '1'-norm of a matrix is the maximum column sum, where the column sum is the sum of the magnitudes of the elements in a given column. The '2'-norm of a matrix is the square root of the maximum eigenvalue of the matrix .
For a positive integer k, the k-norm of a vector is the kth root of the sum of the magnitudes of each element raised to the kth power.
The command with(linalg,norm) allows the use of the abbreviated form of this command.
Examples
See Also
linalg(deprecated)[cond], LinearAlgebra, LinearAlgebra[ConditionNumber], LinearAlgebra[Norm], VectorCalculus[Norm]
Download Help Document