Course detail

Matrices and tensors calculus

FEKT-LMATAcad. year: 2011/2012

Definition of matrix. Fundamental notions. Equality and inequality of matrices. Transposition of matrices. Special kinds of matrices. Determinant, basic attributes. Basic operations with matrices. Special types of matrices. Linear dependence and indenpendence. Order and degree of matrices. Inverse matrix.
Solutions of linear algebraic equations. Linear and quadratic forms. Spectral attributes of matrices, eigen-value, eigen-vectors and characteristic equation. Linear space, dimension. báze. Linear transform of coordinates of vector.
Covariant and contravariant coordinates of vectors and their transformations. Definition of tensor. Covariant, contravariant and mixed tensor. Operation on tensors. Sum of tensors. Product of tensor and real number. Restriction of tensors. Symmetry and antisymmetry of tensors.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. RNDr. Martin Kovár, Ph.D.

Department

Department of Mathematics (UMAT)

Learning outcomes of the course unit

Mastering basic techniques for solving tasks and problems from the matrices and tensors calculus and its applications.

Prerequisites

The knowledge of the content of the subject BMA1 Matematika 1 is required. The previous attendance to the subject BMAS Matematický seminář is warmly recommended.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

Master the bases of the matrices and tensors calculus and its applications.

Specification of controlled education, way of implementation and compensation for absences

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Boček L.: Tenzorový počet, SNTL Praha 1976
Kolman, B., Introductory Linear Algebra, Macmillan Publ. Comp., New York 1991.

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EEKR-ML Master's

    branch ML-SVE , 2 year of study, summer semester, theoretical subject
    branch ML-SVE , 1 year of study, summer semester, theoretical subject
    branch ML-KAM , 2 year of study, summer semester, theoretical subject
    branch ML-KAM , 2 year of study, summer semester, theoretical subject
    branch ML-TIT , 2 year of study, summer semester, theoretical subject
    branch ML-TIT , 1 year of study, summer semester, theoretical subject
    branch ML-EVM , 2 year of study, summer semester, theoretical subject
    branch ML-EVM , 1 year of study, summer semester, theoretical subject
    branch ML-EST , 2 year of study, summer semester, theoretical subject
    branch ML-EST , 1 year of study, summer semester, theoretical subject

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. RNDr. Martin Kovár, Ph.D.

Syllabus

Definition of matrix, fundamental notion. Transposition of matrices.
Determinant of quadratic complex matrix.
Operations with matrices. Special types of matrices. Inverse matrix.
Matrix solutions of linear algebraic equations.
Linear, bilinear and quadratic forms. Definite of quadratics forms.
Spectral attributes of matrices.
Linear space, dimension.
Linear transform of coordinates of vector.
Covariant and contravariant coordinates of vector.
Definition of tensor.
Covariant, contravariant and mixed tensor.
Operation with tensors.
Symmetry and antisymmetry of tensors of second order.

Exercise in computer lab

18 hod., compulsory

Teacher / Lecturer

doc. RNDr. Martin Kovár, Ph.D.

Syllabus

Operations with matrices. Inverse matrices. Using matrices for solving systems of linear algebraic equations.
Spectral properties of matrices.
Operations with tensors.