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Ch7 Kreyszig Linear Algebra

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8/26/2016
Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
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Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
Pages 274-275
Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
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Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
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Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Anti-symmetric matrix
Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Scalar matrices
Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Case study
Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Case study
Linear system
Electrical network
Use Kirchhoff’s current law (KCL)
And Kirchhoff’s voltage law (KVL)
Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Page 294a
Inverse matrix
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Advanced Engineering Mathematics by Erwin Kreyszig
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Page 294c
Silahkan baca buku untuk
mendapatkan Interpretasi Geometris
dari solusi-solusi tersebut
Advanced Engineering Mathematics by Erwin Kreyszig
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Exactly one solution
Gauss
elimination
Infinitely many solution
No solution
Advanced Engineering Mathematics by Erwin Kreyszig
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Existence and Uniqueness of Solutions?
Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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1 2 3
4 5 6
2 4 6
1 2 3
A  4 5 6 , B1  1 2 3 , B2  4 5 6 , B3  3 3 3
7 8 9
7 8 9
7 8 9
7 8 9
(1) 1 2 3
4 5 6
(1)(2)
A  (2) 4 5 6 

 B1  1 2 3
(3) 7 8 9
7 8 9
(1) 1 2 3
2 4 6
2*(1)
A  (2) 4 5 6 (1)

 B2  4 5 6
7 8 9
(3) 7 8 9
.
(1) 1 2 3
1 2 3
(2)(2)(1)
A  (2) 4 5 6 
 B3  3 3 3
(3) 7 8 9
7 8 9
B1, B2 and B3 are all row equivalent to A
Advanced Engineering Mathematics by Erwin Kreyszig
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Rank of A is 2 because the first two rows are linearly independent.
Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Note:
• The dimension of the row space is called the rank of the matrix A
• The null space of the matrix A is the set of all n-dimensional column vector x
such that A x = 0
Advanced Engineering Mathematics by Erwin Kreyszig
Copyright  2007 John Wiley & Sons, Inc. All rights reserved.
Theorem 1 Elementary row operations do not change the row
space of a matrix
Theorem 2 If a matrix A is in row echelon form, then the nonzero rows of A are linearly independent
Corollary The rank of a matrix is equal to the number of nonzero
rows in its row echelon form
Theorem 3 The rank of a matrix A plus the nullity of A equals the
number of column of A
Row Echelon Form
Example
nonzero row
zero row
Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Advanced Engineering Mathematics by Erwin Kreyszig
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Determinant?
Solution
x1 
x1 
DETERMINANT
a22 b1  a12 b2
a11a22  a21a12
a11b1  a21b2
a11a22  a21a12
Advanced Engineering Mathematics by Erwin Kreyszig
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Pages 310-311b
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Advanced Engineering Mathematics by Erwin Kreyszig
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Pages 317-318a
Basic idea:
AX  I
   A I
A
Continued
Advanced Engineering Mathematics by Erwin Kreyszig
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