MA1207 Numerical Analysis

The student should get oneself knowledge in numerical methods to evaluate solutions of such mathematical tasks that cannot be computed analytically. Within telecommunications, signal processes, etc. some technical problems are formulated by means of mathematical models that contain large sets of data, often given as estimates. To find approximated solutions for these problems with the greatest accuracy one studies the technique of building algorithms consisted of regularly repeated steps.

Prerequisites

Calculus MA1102, 15 credit points and Linear Algebra MA1106, 7,5 credit points

Read more about general admission requirements.

Content

• Error analysis
• Numerical methods in linear algebra: solutions of linear equation systems, Inverse matrix, eigen value problems
• Numerical methods applied to non-linear problems: solutions of non-linear equations and non-linear equation systems,
interpolation of functions and point sets, the least square method, numerical differentiation and integration, solutions of ordinary differential equations, solutions of partial differential equations.

Learning outcomes

On completion of the course the student will be able to:

• Learn numerical algorithms of basic mathematical models mentioned in the contents
• Select the algorithms that converge to solutions in the most effective way
• Compose different algorithms to solve complex problems
• Be able to solve numerical problems with a computer.

Generic Skills

The following generic skills are trained in the course:
• Skills in working in interdisciplinary teams
• Skills in expressing problems in English

Course literature and other teaching material

Course literature and other teaching material

Learning methods

The teaching comprises lectures and exercises/laboratory lesson. Teamwork is desirable when solving problems of the laboratory lesson. The project has to be solved individually.

Work placement

No work placement is included in the planned learning activities. BTH is aiming for a close contact with the surrounding community when developing courses and programmes.

Teachers

Examiner
Robert Nyqvist

Course Manager
Robert Nyqvist

Teacher(s)
Robert Nyqvist

Planned learning activities

Lectures

Time allocation

On average, a student should study 200 hours to reach the learning outcomes. This time includes all the various available learning activities (lectures, self studies, examinations, etc.). This estimation is based on the fact that one academic year counts as 60 ECTS credits, corresponding to an average student workload of 1 600 hours. This may vary individually.

Assessments

Code	Title	ECTS credits	Grade
1205	Laboration	3.5	U/G
1215	Written exam1	4	F/P/3/4/5

¹ Determines the final grade for the course, which will only be issued when all components have been approved.

Grading

The course will be graded Fail, Pass, 3, 4 or 5 .

On request grades according to ECTS will be given.

Future exams

Exam date	Parts	Entry dates	Responsible	Place	Time
2013-06-07	1215	2013-05-08 - 2013-05-24	RNY	Karlskrona	09:00 - 14:00
2013-08-23	1215	2013-07-24 - 2013-08-09	RNY	Karlskrona
2014-01-10	1215	2013-12-11 - 2013-12-27	RNY	Karlskrona

To participate in a centrally coordinated examination, you must enroll in Student's Portal, no later than fifteen days before the examination.

Time and location for the examination will be published about 5 days in advance.

There might be other scheduled examinations. Information concerning these examinations are available in It's Learning or at other places that the person who is responsible of the course will refer to.

Course Evaluation

The course manager is responsible for the views of students on the course being systematically and regularly gathered and that the results of the evaluations in various forms affect the form and development of the course.