Subjects

Your browser does not support JavaScript, or its support is disabled. Some features may not be available.

Linear Algebra 2 - NMAI058

Title:	Lineární algebra 2
Guaranteed by:	Department of Applied Mathematics (32-KAM)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2019
Semester:	summer
E-Credits:	5
Hours per week, examination:	summer s.:2/2, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech, English
Teaching methods:	full-time

Guarantor:	prof. Mgr. Milan Hladík, Ph.D. doc. Mgr. Petr Kolman, Ph.D.
Class:	Informatika Bc.
Classification:	Mathematics > Algebra
Is incompatible with:	NALG086, NUMP004, NUMP003

Opinion survey results Examination dates SS schedule Noticeboard

Annotation -

Last update: FIALA/MFF.CUNI.CZ (17.02.2010)

Continuation of MAI057 - special matrices, determinants, eigenvalues, examples of applications of linear algebra.

Course completion requirements -

Last update: prof. Mgr. Milan Hladík, Ph.D. (14.12.2022)

To get the tutorial credit, it is necessary to get at least 120 points (out of 240 possible). Points can be obtained throughout the semester from tests and homework assignments. Specification is provided by the particular tutorial teacher.

Those students who get at least 80 points can obtain the required points by solving additional homeworks or passing an additional test (according to the teacher's instructions).

In specific situations (long-term illness, stay abroad, etc.) the tutorial teacher may set individual conditions for obtaining the credit.

Obtaining the tutorial credit is a necessary condition for taking the exam.

Literature -

Last update: prof. Mgr. Milan Hladík, Ph.D. (22.11.2012)

W. Gareth. Linear Algebra with Applications. Jones and Bartlett Publishers, Boston, 4th edition, 2001.

C. D. Meyer. Matrix analysis and applied linear algebra. SIAM, Philadelphia, PA, 2000. http://www.matrixanalysis.com/DownloadChapters.html

G. Strang. Linear algebra and its applications. Thomson, USA, 4rd edition, 2006.

Requirements to the exam -

Last update: doc. Mgr. Jan Hubička, Ph.D. (13.06.2022)

There will an examination consisting of a written and oral part.

The written part involves several exercises. The oral part involves discussion of solutions to the set problems and additional questions on topics covered in lectures and classes.

Result of tests accomplished during the teaching period may be taken into account at the exam.

Class credits ("zapocet") are prerequisite for taking the examination

Syllabus -

Last update: prof. Mgr. Milan Hladík, Ph.D. (28.03.2022)

Inner product spaces:

norm induced by an inner product

Pythagoras theorem, Cauchy-Schwarz inequality, triangle inequality

orthogonal and orthonormal system of vectors, Fourier coefficients, Gram-Schmidt orthogonalization

orthogonal complement, orthogonal projection

the least squares method

orthogonal matrices

Determinants:

basic properties

Laplace expansion of a determinant, Cramer's rule

adjugate matrix

geometric interpretation of determinants

Eigenvalues and eigenvectors:

basic properties, characteristic polynomial

Cayley-Hamilton theorem

similarity and diagonalization of matrices, spectral decomposition, Jordan normal form

symmetric matrices and their spectral decomposition

(optionally) companion matrix, estimation and computation of eigenvalues: Gershgorin discs and power method

Positive semidefinite and positive definite matrices:

characterization and properties

methods: recurrence formula, Cholesky decomposition, Gaussian elimination, Sylvester's criterion

relation to inner products

Bilinear and quadratic forms:

forms and their matrices, change of a basis

Sylvester's law of inertia, diagonalization, polar basis

Topics on expansion (optionally):

eigenvalues of nonnegative matrices

matrix decompositions: Householder transformation, QR, SVD, Moore-Penrose pseudoinverse of a matrix