Information Processing in Technical Systems

2019/2020

Content, progress and pedagogy of the module

Learning objectives

Knowledge

• have knowledge about modern statistical signal processing and its application to information processing systems
• have knowledge about information and coding theory and their application to information and communication technology systems and/or machine learning and its applications to technical science

Skills

• must be able to perform an analysis of complex theoretical problems, where there is a need for tools from statistical signal processing, information theory or machine learning
• must be able to handle problems with noisy data and signals
• must be able to design algorithms solving a given technical problem

Competences

Competencies:
• must be able to discuss and reason at the given level using mathematical terms from modern signal processing, as well as information theory, coding theory or machine learning
• must be able to both orally and in writing to present precise and reproducible documentation for the solutions developed

Type of instruction

Project work.

Extent and expected workload

This is a 15 ECTS project module and the work load is expected to be 450 hours for the student.

Exam

Exams

Name of examInformation Processing in Technical Systems
Type of exam
Oral exam based on a project
ECTS15
Permitted aids
All written and all electronic aids
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleInformationsbehandling i teknologiske systemer
Module codeF-MTK-K1-1
Module typeProject
Duration1 semester
SemesterAutumn
ECTS15
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Study BoardStudy Board of Mathematics, Physics and Nanotechnology
DepartmentDepartment of Mathematical Sciences
FacultyFaculty of Engineering and Science