NORM Norm Calculation

Section: Array Generation and Manipulations

Usage

Calculates the norm of a matrix. There are two ways to use the 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

For a vector, the regular norm calculations are performed:

Examples

Here are the various norms calculated for a sample matrix
--> A = float(rand(3,4))
A = 
  <float>  - size: [3 4]
 
Columns 1 to 4
 0.426610678  0.075468481  0.871337116  0.487616807  
 0.879925549  0.154911667  0.373149037  0.475030541  
 0.041696656  0.165778294  0.552217603  0.506726503  
--> norm(A,1)
ans = 
  <float>  - size: [1 1]
 1.7967038  
--> norm(A,2)
ans = 
  <float>  - size: [1 1]
 1.5921172  
--> norm(A,inf)
ans = 
  <float>  - size: [1 1]
 1.8830168  
--> norm(A,'fro')
ans = 
  <float>  - size: [1 1]
 1.7142895  

Next, we calculate some vector norms.

--> A = float(rand(4,1))
A = 
  <float>  - size: [4 1]
 
Columns 1 to 1
 0.68404633  
 0.20355032  
 0.90988815  
 0.69708711  
--> norm(A,1)
ans = 
  <double>  - size: [1 1]
 2.4945719242095947  
--> norm(A,2)
ans = 
  <float>  - size: [1 1]
 1.3502514  
--> norm(A,7)
ans = 
  <double>  - size: [1 1]
 0.9436675093733905  
--> norm(A,inf)
ans = 
  <float>  - size: [1 1]
 0.90988815  
--> norm(A,-inf)
ans = 
  <float>  - size: [1 1]
 0.20355032