ELEZOVI LINEARNA ALGEBRA PDF

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Analitička geometrija i linearna algebra. Bodovna vrijednost (ECTS) Elezović, N.: Linearna algebra, Element, Zagreb (više izdanja). desetak. Elezović, N. Check whole offer from author NEVEN ELEZOVIĆ. cart add to wishlist. LINEARNA ALGEBRA – ZBIRKA ZADATAKA – 3. izdanje – neven elezović, andrea aglić. Elezović, Neven. Overview . Matematika 3: zadaci s pismenih ispita by Neven Elezović(Book) Linearna algebra: s 58 crteža by Neven Elezović(Book).

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Normed vector space Linear operators and their matrix representation. Optional literature at the time of submission of study programme proposal. Linear AlgebraElement, Zagreb, multiple editions. Master the fundamental vector algebra and analytic geometry concepts and apply them in limearna tasks; Identify and differentiate between types of second order surfaces; Explain the concepts of matrices and determinants, list their properties and use them in computations with matrices and determinants; Distinguish methods for solving systems of linear equations and apply the appropriate method to solve a given system; Describe the method of least squares and argue its application in solving tasks; Define the terms of eigenvalues and eigenvectors and know their typical applications; Describe and implement the concepts of diagonalization and orthogonal diagonalization of a matrix.

In revising during lectures. Linear Algebra WorkbookElement, Zagreb, multiple editions some ten 2. General Competencies Acceptance of concepts and zlgebra in linear algebra on more advanced level.

N.elezovic – Linearna Algebra

Studijski program preddiplomski, diplomski, integrirani preddiplomski 1. Level of application of e-learning level 1, 2, 3percentage of online instruction max. Basic properties, computation of determinants. Learning Outcomes list basic notions of linear algebra describe basic notions and results of linear algebra derive basic results of linear algebra explain the connection between linear algebra and problems of stability describe the properties of matrix norm convert a linear system of differential equations into a matrix form.

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You are hereby informed that cookies are necessary for the web site’s functioning and that by continuing to use this web sites, cookies will be used in cooperation with your Web browser. Linear Algebra Learning Outcomes describe and apply linear algebra basic concepts and methods demonstrate fundamental skills of matrix calculus and solving linear systems of equations apply fundamental knowledge of vector analysis and space analytic geometry demonstrate basic knowledge of vector spaces and linear operators demonstrate an ability to express mathematical ideas and abstract thinking in linear algebra demonstrate an ability to basic problem solving and reaching conclusions in linear algebra use methods of linear algebra in engineering.

Exercise appropriate judgements on the basis of performed calculation processing and interpretation of data obtained by means of surveying and its results. Laplace’s rule, Elementary transformations, rank of a matrix, linear independence and rank.

Quality assurance methods that ensure the acquisition of exit competences Class attendance. Lecturers algfbra Charge Prof.

Linearna algebra: zbirka zadataka | Neven Elezović, Andrea Aglić Aljinović | digital library Bookfi

Lecturers in Charge Prof. Learning outcomes at the level of the programme to which the course contributes. Quality assurance methods that ensure the acquisition of exit competences. Learning outcomes at the level of the programme to which the course contributes Demonstrate competences in wlezovi principles, procedures of computing and visualising the surveying data.

Login Hrvatski hr English. Activity on the system for e-learning. Dopunska literatura u trenutku prijave prijedloga studijskoga programa Anton, H. Use the system for e-learning. Forms of Teaching Lectures the lectures include auditory exercises Exams five homeworks Exercises included in the lectures Consultations twice per week E-learning matrix transformations of the plane http: Week by Week Schedule Matrices. Grading System ID Course enrolment requirements and entry competences required for the course.

Linearna zavisnost i linearna nezavisnost vektora. Diagonalization of quadratic forms. Characterization of regular matrices Elementary transformations, rank of a matrix, linear independence and rank. Demonstrate competences in theoretical principles, procedures of computing and visualising the surveying data. Exercise appropriate judgements on the basis of performed calculation processing and interpretation of data obtained by means of surveying and its results.

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Course enrolment requirements and entry competences required for the course. Pri ponavljanju gradiva na predavanjima. Registar bagatelne nabave u Godina studija Prva, I semestar 1. Pri ponavljanju gradiva na predavanjima. You are hereby informed that cookies are necessary for the web site’s functioning and that by continuing to use this web sites, cookies will be used in cooperation with your Web browser.

Dopunska literatura u trenutku prijave prijedloga studijskoga programa Anton, H. Status of the course compulsory 1. Use algeba acquired mathematical and numerical skills of analytical geometry and linear algebra linewrna solve problems in the field of study.

Required literature available in the library and via other media. Linear Algebra WorkbookElement, Zagreb, multiple editions some ten 2. Vector and scalar projections of one vector on another Cross product of two vectors and mixed product of three vectors, Radius-vector.

Forms of Teaching Lectures Lectures are held in two cycles, 4 hours per week Exercises Exercises are held in two cycles, 4 hours per week Partial e-learning Homework is accessible on course web-page. The implementation of a single university Questionnaire for evaluating teachers prescribed by the Senate. Number of copies in the library.

Homogeneous and nonhomogeneous systems, Rank of a system and rank of extended matrix Rank of a system and rank of extended matrix, Cramer’s rule. Expected enrolment in the course 90 1. Ispitni rokovi u ak. Hamilton-Cayley’s theorem, Schur’s theorem. Godina studija Prva, I semestar 1. Uvjeti za upis predmeta i ulazne kompetencije potrebne za predmet.