ELEZOVI LINEARNA ALGEBRA PDF

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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Hamilton-Cayley’s theorem, Schur’s theorem. Problem solving during exercises. Course algebea requirements and entry competences required for the course Admission requirements: The implementation of a single university Questionnaire for evaluating teachers prescribed by the Senate.

Linearna zavisnost i linearna nezavisnost vektora. Solving linear systems using the Gauss-Jordan reduction. Expected enrolment in the course 90 1.

Laplace’s rule, Elementary transformations, rank of a matrix, linear independence and rank. Course enrolment requirements and entry competences required for the course.

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.

Summary of Analytical Geometry and Linear Algebra

Pri ponavljanju gradiva na predavanjima. Course content broken down in detail by weekly class schedule syllabus.

Availability via other media. Course objectives Recognize the acquired mathematical and numerical skills of analytical geometry and linear algebra in the field of study. Mutual position of two planes. Learning outcomes at the level of the programme to which the course contributes.

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Informacije o e-kolegiju

Naslovnica E-kolegiji Studiji Studij geodezije i geoinformatike – preddiplomski 1. Vectors in coordinate systems, Dot product.

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. Basic properties, computation of determinants. Demonstrate competences in theoretical principles, procedures of computing and visualising the surveying data.

Number of copies in the library. Grading System ID Learning outcomes expected at the level of the course 4 to 10 learning outcomes Master the fundamental vector algebra and analytic geometry concepts and apply them in solving tasks; Identify and differentiate between types of second order surfaces; Explain the concepts of matrices and determinants, list their properties and linsarna 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 algbera.

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.

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Bodovna vrijednost ECTS 5 1. Dopunska literatura u trenutku prijave prijedloga studijskoga programa Anton, H. Learning outcomes expected at the level of the course 4 to 10 learning outcomes Master the fundamental vector algebra and analytic geometry concepts and apply them in solving 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.

Dostupnost putem ostalih medija. Apply knowledge of mathematics and physics for the purpose of recognizing, formulating and solving of problems in the field of geodesy and geoinformatics. Lecturers in Charge Prof. Bodovna vrijednost ECTS 5 1. Study programme undergraduate, graduate, integrated Bachelor Study 1. Optional literature at the time of submission of study programme proposal.

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Hyperspace, half-space Eigenvalues and eigenvectors. Uvjeti za upis predmeta i ulazne kompetencije potrebne za predmet.