Postgraduate Course: Digital Signal Processing Laboratory (MSc) (PGEE11108)
|School||School of Engineering
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||The course will teach students to solve simple problems in the areas of communications and signal processing in a MATLAB environment. The course will reinforce material taught in the co-requisite courses and provide practical experience of signal and image processing implementation in preparation for the project. The course will be composed of programming sessions and course assignments covering discrete time signal analysis, communications and image processing.
1. A set of assessed programming sessions run weekly covering:
- Introduction to signal processing in MATLAB;
- generating time domain signals;
- simulating continuous and sampled signals;
- calculating the DFT, its properties and implementation;
- signal and image filtering;
- power spectral density estimation.
2. Course assignments to be completed outside of lab hours. Example exercises could be: simulating an adaptive noise cancellation problem, estimating frequencies and noise power in a time domain signal, simulating a simple modulation / demodulation and detection scheme.
Course Delivery Information
|Academic year 2017/18, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Supervised Practical/Workshop/Studio Hours 30,
Summative Assessment Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||100% coursework: marked assignments
||Feedback is provides on marked assignments.
|No Exam Information
| Students are required to formulate solutions to practical communications, signal and image processing problems and to code, debug and run these in MATLAB. Specific learning outcomes are:
1. Understanding of how to use MATAB to simulate and analyze signal and image processing algorithms.
2. Reinforce the practical understanding of other 1st semester courses, Discrete-Time Signal Analysis PGEE11026; Digital Communication Fundamentals PGEE11025; Statistical Signal Processing PGEE11027; Image Processing PGEE11021 through practical labs and marked assignments.
|Online MATLAB resources and lecture notes for co-requisite courses.|
|Graduate Attributes and Skills
|Keywords||Signal Processing,Communications,Image Processing
|Course organiser||Dr Michael Davies
|Course secretary||Miss Megan Inch
Tel: (0131 6)51 7079