- •1.Matrices. Classification of matrices. Operations over matrices: addition of matrices, multiplication of a matrix on number.
- •2. Matrices. Multiplication of matrices.
- •3. Determinants. Calculating determinants of the second and third order.
- •5. Properties of determinants. Decomposing a determinant of the fourth order on a row (or column). Notion of determinant of the n-th order.
- •Notion of a determinant of the n-th order
- •7.Inverse matrix. Finding the inverse matrix.
- •Compute the determinant of the matrix а (if it equals zero then there is no inverse matrix).
- •6.Systems of linear equations.(Cramer rule)
- •8.Matrix representation of a system of linear equations. Finding solutions of a system of linear equations by method of inverse matrix.
- •9.Rank of a matrix. Finding the rank of a matrix by two methods.
- •10.Criterion for compatibility of a system of linear equations (Theorem of Kronecker-Capelli). Example of determining the compatibility of a system by this theorem.
- •13Vectors (in the geometric space). Changing the coordinates of a vector at replacement of a basis and the origin of coordinates.
- •14Transition between orthonormal systems of coordinates on plane. Right (left) oriented pair of vectors on plane.
- •15 Linear dependence of vectors in the geometric space (plane and line). Theorems on properties of linearly dependent vectors.
- •16. Basis in the geometric space (plane and line). The coordinates of a vector in a basis.
- •17. Cartesian system of coordinates. Radius-vector of a point. Finding the coordinates of a point dividing a segment in some ratio.
- •18. Complex numbers. Actions over complex numbers. Algebraic and trigonometric forms of a complex number.
- •20. Dimension and a basis of a linear space. Isomorphism of linear spaces.
- •19. Linear space. Theorems on properties of a linear space. Linearly independent vectors in a linear space.
- •Linearly independent vectors. Let X, y, z, …, u be vectors of a linear space .
- •21. Transformation of coordinates at transition to a new basis in a linear space. Theorems on transition matrix and formulas of transformation of coordinates.
- •22. Subspaces of a linear space. Linear hull of vectors. Intersection, union, sum and direct sum of subspaces.
- •23. Fundamental system of solutions of a homogeneous system of equations. Subspaces formed by solutions of a homogeneous linear system of equations.
- •24. Linear transformations. Examples of linear transformations. Actions over linear transformations.
- •Actions over linear transformations
- •28.The image and kernel of a linear operator.
- •29Linear mapping. Injective and surjective linear mappings. Matrix of a linear mapping.
- •30Linear functionals. The components of a linear functional. Dual space of linear functional
- •28.The image and kernel of a linear operator.
3. Determinants. Calculating determinants of the second and third order.
Property1. The value of determinant doesn’t change if we replace all its rows by corresponding columns and vice versa.
Property2. if we replace any two rows(columns) then the determinant will change its sign.
Corollary. A determinant having two identical rows (columns) is equal to zero.
Property 3. If all the elements of a row (column) of a determinant are multiplied on the same non-zero number “m”. Then the determinant value increases (decreases) in “m” times.
Corollary. If all the elements of a row(column) of a determinant have a non-zero common multiplier it can be taken out the determinant.
The
determinant of the second order which
corresponds to a square matrix of the second order А(2;
2) =
is the number denoted by the following symbol =
and which is equal to:
=
This is illustrated by the following scheme:
The
determinant of the third order
which corresponds to a square matrix of the third order А(3;
3) =
is the number denoted by the following
symbol
=
and which is equal to
(2)
For calculation of determinants of the third order is convenient to use «the triangle rule» which follows from the formula (2) and symbolically is written as:
4. Minors, cofactors. Finding minors and cofactors of a matrix.
The
minor
М
of the element a
of
a square matrix A(n;
n)
is the determinant obtained from the given one by deletion of the
i-th
row and the j-th
column.
For
a determinant of the second order
=
:
For
a determinant of the third order =
:
М
=
;
M
=
and etc.
The
cofactor
А
of the element а
of a square matrix А(n;
n)
is the minor М
multiplied on the number (–1)
,
i.e. А
=
(–1)
М
.
Thus,
if the sum of indices i
+ j
of the element а
is even then the cofactor of this element coincides with its minor
by sign, i.e. А
М
;
if the sum of indices i
+ j
of the element а
is odd then the cofactor of this element is opposite to its minor by
sign, i.e. А
=
– М
.
5. Properties of determinants. Decomposing a determinant of the fourth order on a row (or column). Notion of determinant of the n-th order.
Property 1. The value of a determinant doesn’t change if we replace all its rows by the corresponding columns and vice versa.
Property 2. If we replace any two neighbouring rows (columns) then the determinant will change a sign.
Corollary. A determinant having two identical rows (columns) is equal to zero
Property 3. If all the elements of a row (column) of a determinant are multiplied on the same non-zero number «m» then the determinant value increases (decreases) in «m» times.
Corollary 1. If all the elements of a row (column) of a determinant have a non-zero common multiplier, it can be taken out the determinant sign.
Corollary 2. A determinant at which elements of two arbitrary rows (columns) are proportional respectively is equal to zero.
Property 4. Let each element of an arbitrary row (column) be the sum of two addends. Then the determinant is equal to the sum of two determinants such that the corresponding row (column) of the first determinant consists of the first addends, and the corresponding row (column) of the second determinant consists of the second addends.
Corollary. A determinant doesn’t change its value if all the elements of a row (column) are added to (subtracted from) the corresponding elements of an arbitrary other row (column) multiplied on the same non-zero number.
Theorem 1. If all the elements of an arbitrary i–th row (either j–th column) of a determinant but aij are equal to zero, the determinant is equal to the product of this non-zero element aij on its cofactor Aij, i.e. = aij Aij.
Theorem 2. A determinant is equal to the sum of products of elements of an arbitrary row (column) on their cofactors. This operation is called a decomposition of a determinant on a row (column).
