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LECTURE 4. Rank of a matrix. Theorem of Kronecker-Capelli. The Gauss method.

 

a

a

...

a

 

 

11

12

 

1n

Consider a matrix of dimension m x n:

a21

a22

...

a2n

A(m; n)

 

 

 

 

 

...

...

...

...

 

 

 

 

 

 

 

 

am2

...

 

 

 

am1

amn

Take a natural number k such that k m and k n. Choose in A arbitrary k rows and k columns. Then obtain a square matrix of the k-th order. The determinant of this matrix is called minor of the k-th order of the matrix A. The number of all minors of different orders can be great even for a matrix of non-large dimension. For example, a matrix of dimension 4 x 5 has 5 minors of the fourth order, 40 minors of the third order, 60 minors of the second order and 20 minors of the first order (minors of the first order coincide with elements of a matrix).

Definition. Rank of a matrix A is the greatest order of its non-equal to zero minors. Rank of a matrix is denoted by Rank A or r(A).

This definition implies that for calculation of rank of a matrix it is necessary to compute all minors of all orders of a matrix A, choose non-equal to zero minors and determine which one from them has the greatest order. However such a method of calculating the rank of a matrix is useless due to a great number of calculations because there can be a lot of minors at a matrix. For example, a matrix A(4; 5) has 125 minors.

Theorem. Rank of a matrix doesn’t change if:

1)All the rows are interchanged by the corresponding columns and vice versa;

2)Interchange two arbitrary rows (columns);

3)Multiply (divide) each element of a row (column) on the same non-zero number;

4)Add to (subtract from) elements of a row (column) the corresponding elements of any other row (column) multiplied on the same non-zero number.

The notion of rank of a matrix is used for investigation of compatibility of a system of linear equations. Consider a system of m linear equations with n variables x1, x2, x3, …, xn

a11x1 a12 x2 ...

a1n xn b1 ,

 

 

 

 

 

 

 

a2n xn b2 ,

a21x1 a22 x2

..............................................

 

 

 

 

 

 

 

 

 

 

 

 

a

m1

x a

m2

x

2

...

a

mn

x

n

b .

 

1

 

 

 

 

m

The basic and extended matrices of the system are the following:

a

a

...

a

 

a

a

...

a

b

 

11

12

 

1n

11

12

 

1n

1

 

a21

a22

...

a2n

a21

a22

...

a2n

b2

 

A(m; n) ...

...

...

...

,

C(m; n 1) ...

...

... ...

... .

 

 

 

 

 

 

 

 

 

 

 

 

am2

...

 

 

 

am2

...

amn

 

 

am1

amn

am1

bm

A criterion for compatibility of a system of linear equations is expressed by Kronecker-Capelli theorem. This theorem gives an effective method permitting in finitely many steps to determine whether the system is compatible or not.

Theorem of Kronecker-Capelli. A system of linear equations is compatible iff the rank of a basic matrix A equals the rank of an extended matrix C, i.e. Rank A = Rank C. Moreover:

1)If Rank A = Rank C = n (where n is the number of variables in the system) then the system has a unique decision.

2)If Rank A = Rank C < n then the system has infinitely many decisions.

Literature:

S. Lipschutz, Theory and problems of linear algebra, Schaum’s outline series, 1987. Chapter 3, paragraph 1-6, pp.56-67.

Control questions:

1.Rank of a matrix.

2.Gauss method.

3.Theorem of Kronecker-Capelli.

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