StudyQA — Master: Electrical Engineering with Emphasis on Signal Processing — Blekinge Institute of Technology (Page 33)

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Description Contents Requirements

The objective of the programme is to prepare for qualified development work in industry as well as provide a basis for research studies. The students meet and work closely with researchers in the field of Signal Processing and will get a thorough understanding in these areas.

After finishing the studies the student will be able to apply the knowledge in a range of situations for an analysis of problems as well as creation of solutions. The student will be able to select, design and apply a range of complimentary and cohesive tools and concepts in the area

The programme is mainly focused on adaptive, image processing and acoustic signal processing. The student will learn to implement methods in industrial areas in the field of noise and vibration control, speech coding, speech enhancement, image processing, etc. Example of important courses: Multidimensional Signal Processing, Computer vision, Sound- and Vibration Analysis, Adaptive Signal Processing, Optimal Signal Processing, and Neural Networks.

The studies will mainly be carried out on campus to make it possible for the students to work close to the researchers of chosen emphasis. The education will include both theory and practical applications and the student will work both independent and integrate in to team as well. The programme will be finished by a master thesis work (30 credit points) which normally will be done at the industry or in close cooperation with the industry.

In order to get the master´s degree a student has to complete 90 credit points (1.5 years) courses plus a 30 credit points (0.5 year) master thesis work, totally 2 years. One credit point (högskolepoäng) in the Swedish system corresponds to one credit point in the European Credit Transfer System (ECTS).

The programme is based on that the student has a bachelor of science in the area of either electrical engineering or computer engineering.

Aims and learning outcomes

In addition to the aims regulated nationally the following aims have been set for the programme.

On completion of the programme the student will:

* show knowledge and understanding in the electrical engineering area, mainly in the area of Signal Processing.
* show knowledge and understanding of current trends and problems within the area of Signal Processing.
* show ability to search, evaluate and use information in an independent way to be able to learn during both future studies and at working life.
* show ability to, in an independent way, broad the own knowledge into new areas within the area of Signal Processing and also have the ability to analyze problems and develop new methods and techniques as well.

Learning and education

The programme begins with an advanced mathematical introduction and a mandatory basic course within the emphasis to give base for future studies at the programme.

During the last semester at the programme the student will perform a master thesis work which will combine knowledge from the courses at the programme. To gain and ensure high quality at the master thesis work, all students have to study a comprehensive course in research methodology.

The language of instruction and the language of learning resources are in English.

The programme includes course work of 90 ECTS and a Masters thesis of 30 ECTS. Total duration of the programme is 2 years which includes four semesters. Each year is divided into four lecture periods (Lp1, Lp2, Lp3 and Lp4). There are twelve courses at the programme and each course is 7.5 ECTS.

During the first year, Lp1, the first two courses Complex Analysis and Transforms and Signal Processing II will form a base for nearly all the courses at the programme. In the next lecture period, Lp2, the course Random Processes will be used in four courses. The course Multidimensional Signal Processing is basically a generalization of the course Signal Processing II into higher dimensions and will give a better understanding of this course. Multidimensional Signal Processing is not a formal prerequisite for future courses but will be an advantage for the coming courses at the programme, especially the image processing courses. During Lp3 at the first year, the two courses Adaptive Signal Processing and Digital Transmission and Radio Communications will complete the base of fundamental knowledge in the signal processing area. You now have a large set of advanced tools for continuing at the programme.

The programme has three main areas (where some courses belong to the base of fundamental knowledge already studied above).

Adaptive signal processing area:

* Adaptive Signal Processing, Lp3, first year (mandatory)
* Applied Adaptive Signal Processing, Lp4, first year (mandatory)
* Optimal Signal Processing, Lp1, second year (optional)
* Neural Networks, Lp2, second year (mandatory)

Image processing area:

* Multidimensional Image Processing, Lp2, first year (mandatory)
* Digital Image Processing and Analysis, Lp4, first year (optional)
* Computer Vision, Lp1, second year (optional)

Sound and Vibrations area:

* Sound and Vibrations Analysis, Lp4, first year (optional)
* Experimental Modal Analysis, Lp1, second year (optional)

In the next lecture periods (first year, Lp4, second year Lp1 and second year Lp2) you will select from these main areas.

During Lp1, second year, the course Research Methodology with emphasis on Electrical Engineering will focus on how to prepare for the Masters thesis.
During the next lecture period, Lp2, second year, you can choose between three optional courses that are useful for all areas above:

* Advanced Filter Design (optional)
* Digital Signal Processors (optional)
* Applied Signal Processing (optional)

During the last semester at the programme (Lp3 and Lp4, second year), the Masters thesis will let you apply your theoretical and practical knowledge from all the previous courses at the programme in a major project within radio communications.

For admission to the study programme, a Bachelor's degree (180 credits) with one of the main fields of study Electrical Engineering or Computer Technology is required. The Bachelor's degree should comprise at least 30 credits mathematics where multidimensional analysis, transform theory and mathematical statistics are included. Further, a higher education qualification should include signal processing, programming, computer network and telecommunications. English B.Admission CriteriaGENERALThis method has the purpose of assessing the applicants competency for studies at, among others, the Master Programmes in Electrical Engineering, Computer Science and Software Engineering.BASES FOR RANKING OF APPLICANTPrevious university studies and English.DETAILS ON BASES FOR SELECTION:The first step of the ranking process is an assessment of the relevance of the area and specialisation of the applicants previous university studies to the applied programme. This assessment is made in three categories: minimal relevance = merit points 0, average relevance = merit points 0.5, high relevance = merit points 1.Finally, the applicants TEOFL or IELTS level in English is normalised to a value between 0 and 1, where 0 is the minimum level to pass the prerequisites of the applied programme and 1 is the maximum level of the test. Applicants who are not required to prove their English skills with TOEFL or IELTS tests will get the merit point 1.These two merit point values are added to a total merit value between 0 and 2MAXIMUM MERIT RANKING:A maximum of 2 merit points will be given, according to the above given details.WORK METHOD:Applications that are accepted for review based on the basic requirements for the programme will be ranked according to the details above. If not all applicants with the same lowest merit point can be admitted, a preference is given to the gender that is least represented at the programme, and if further selection is needed lots will be drawn. English Language Requirements IELTS band: 6.5 TOEFL paper-based test score : 575 TOEFL iBT® test: 90