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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2019/2020

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DRPS : Course Catalogue : Edinburgh College of Art : Music

Postgraduate Course: Postgraduate Musical Applications of Fourier Theory and Digital Signal Processing (MUSI11034)

Course Outline
SchoolEdinburgh College of Art CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course aims to describe the mathematical underpinnings of Fourier theory, and digital signal processing, especially with regard to music and audio applications. The emphasis is on algebraic work, and on practical computation for sound analysis and synthesis.
Course description Not entered
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2019/20, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Please contact the School directly for a breakdown of Learning and Teaching Activities
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) This course includes 5 summative Components of Assessment, spread throughout the teaching semester.

Component 1 (10% of course mark):

An in-class test around the middle of semester. The test covers background mathematics and signal processing concepts studied during the first part of the course.

Component 2 (30% of course mark): End-Semester Class Test

An open book in-class test, which will take place during a timetabled lecture slot near the end of semester. The test covers background mathematics and signal processing concepts studied throughout the course.

Component 3 (10% of course mark): Matlab Programming Exercise

A short computer programming assignment on the basic syntax and methodology of writing efficient and well-formatted Matlab code. This is completed in your own time, to a deadline set in the early-to-mid part of the semester, and is designed to help prepare you for the more extended Components of Assessments that use Matlab programming.

Component 4 (25% of course mark): Matlab Project 1

An extended Matlab programming assignment, where you will bring together the signal processing and computer programming strands of the course to create practically useful audio processing software, to a prescribed remit. This is completed in your own time, to a deadline set in the latter half of the semester.

Component 5 (25% of course mark): Matlab Project 2

A more extended Matlab programming assignment, where you will bring together the signal processing and computer programming strands of the course to create practically useful audio processing software, to a prescribed remit. This is completed in your own time, to a deadline set in the exam period at the end of semester.
Feedback Formative feedback
Each week will be accompanied by a set of tutorial problems covering the key background mathematics and signal processing concepts. You will be expected to work through these problems in advance of the forthcoming lecture. During this lecture, a selection of problems will be worked through, giving you the chance for multiple points of formative feedback throughout the semester. You will be encouraged to contribute to this process by suggesting specific problems and areas of focus.
For the computer programming aspect of the course, you will receive weekly programming workshops, at which you will have the chance for regular verbal feedback and guidance.

Summative feedback
For the class tests (Components 1 and 2) you will receive your marked test scripts, allowing you to see where you have done well, and where you might focus your ongoing study. For the computer programming assignments (Components 3, 4 and 5) you will receive written feedback to explain your mark.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate a technical understanding of Fourier anaylsis, especially as applied to discrete time audio signals, as well as an understanding of the functioning of various audio effects, including chorus, flanging, and phasors.
  2. Evidence an understanding of the short time Fourier transformation, and phase vocoder based time stretching and pitch shifting algorithms, at the algebraic and programming levels.
  3. Demonstrate an understanding of simple digital filter structures as used in audio applications and an understanding of discrete inner product spaces, and the concept of signal orthogonality.
  4. Evidence an understanding of the underpinnings and implications of the audio sampling theorem and have gained facility in the Matlab programming language.
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNot entered
Contacts
Course organiserDr Brian Hamilton
Tel:
Email: Brian.Hamilton@ed.ac.uk
Course secretaryMrs Carrie Parker
Tel: (0131 6)50 2422
Email: Carrie.Parker@ed.ac.uk
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