matlab practice of matrix analysis and processing

 

 

•  3 norm

L₁ Norm (columns and norm) NORM (A, . 1)

L ₂  norm (columns and norm) NORM (A, 2)

RAND = A (5, 5); 
A1 = Rank (A)% rank 
A2 = trace (A)% trace 
A3 = det (A)% determinant 
A4 (A, 2)% 2 = NORM NORM 
---- -------------------------------- 
A1 = 
     5 
A2 = 
    2.8203 
A3 = 
    0.0538 
A4 = 
    2.6379

• 4.1

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X = linsolve(A,B)

X = linsolve(A,B,opts)

[X,r] = linsolve(___)

X = linsolve(A,B) Solving linear equations using one of the following methods  AX = B:

• When  A a square , the linsolve used portion of the main element LU decomposition and elimination method.

• For all other cases, linsolve the QR decomposition and main-element elimination method.

If  A morbidly (for a square) or a rank-deficient (for a rectangular matrix), then the  linsolve warning.

X = linsolve(A,B,opts) Structure used by options  opts appropriate solver determined. opts The field is described matrix  A logic value attribute. For example, if  A is an upper triangular matrix, you can set  opts.UT = true so that  linsolve the use of design as an upper triangular matrix solver. linsolve No test to verify  A whether the  opts specified property.

[X,r] = linsolve(___) Also returns  r, i.e.  A the reciprocal of the number of conditions (for a square) or  A rank (for a rectangular matrix). You can use any combination of the above input parameter syntax. When using this syntax, if the  A loss is sick or rank, linsolve without warning.

A=[1/2 1/3 1/4;1/3 1/4 1/5;1/4 1/5 11/6];
B=[0.95;0.67;0.52];
X = linsolve(A,B)
---------------------------------------------
X =

    1.0202
    1.3193
    0.0006
---------------------------------------------
b3=0.53后
A=[1/2 1/3 1/4;1/3 1/4 1/5;1/4 1/5 11/6];
B=[0.95;0.67;0.53];
X = linsolve(A,B)
cond（A）
---------------------------------------------
X =

    1.0220
    1.3121
    0.0066

years = 102.5850