University of Manchester

School of Computer Science

CS3291: Digital Signal Processing

Lecturer: Barry M.G. Cheetham www.cs.man.ac.uk/~barry

Syllabus: www.cs.man.ac.uk/~barry/mydocs/CS3291/Syllabus

Lecture notes: www.cs.man.ac.uk/~barry/mydocs/CS3291/Notes

Lecture slides: www.cs.man.ac.uk/~barry/mydocs/CS3291/Slides

MATLAB material: www.cs.man.ac.uk/~barry/mydocs/CS3291/DSP_MATLAB

Past exam papers with solutions: www.cs.man.ac.uk/~barry/mydocs/CS3291/Exams

Solutions to selected problems: www.cs.man.ac.uk/~barry/mydocs/CS3291/Solutions

Aims:

Learning Outcomes:

After successfully completing this course students will be able to:

  1. understand the significance of digital signal processing in the fields of computing, telecommunications, multi-media technology and other areas of computer science and Electronic/Electrical Engineering.
  2. understand fundamental concepts such as 'linearity' , 'time-invariance', 'impulse response', 'convolution', 'frequency response', 'z-transforms' and the 'discrete time Fourier transform'. as applied to discrete time signal processing systems.
  3. apply a design technique for FIR type digital filters known as the "windowing method".
  4. apply several design techniques for IIR type digital filters: "pole-zero placement", the "derivative approximation" and the "bilinear transformation" techniques.
  5. use the "MATLAB" language and "signal processing toolboxes" for analysing, designing and implementing digital signal processing (DSP) systems such as digital filters.
  6. specify the "real time" implementation of DSP operations using special purpose fixed point 'DSP microprocessors'.
  7. understand analogue/digital conversion as required for the digital processing of analogue signals.
  8. understand the discrete Fourier transform (DFT), its applications and its implementation by FFT techniques.

Assessment of Learning Outcomes: 2 hour written examination

Contribution to programme learning outcomes: A2, A3, A5, B1, B2, B3, C4

Reading List and Supporting Material: