This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.

Postgraduate Handbook 2015-2016 (archived)

Module ENGI42215: Digital Signal Processing

Department: Engineering

ENGI42215: Digital Signal Processing

Type	Level	Credits	Availability	Module Cap	Location
Tied	4	15	Not available in 2015/2016		Durham

Tied To

H1K709: Communications Engineering

Pre-requisites

Communicational Fundamentals (ENGI30215) or equivalent

Corequisites

Radio and Digital Communications (ENGI41915); Communications Networks (ENGI42015); Engineering Design (ENGI41030); Research and Development Project (ENGI41060)

Excluded Combinations

None

Aims

The course aims to develop computational methods for digital signal processing.

Content

Analysis of Discrete - Time Signals and Systems: Discrete-time signals; poles and zeros; transfer functions; z-transforms; unit circle; stability; inverse z-transform; steady-state frequency response.
Synthesis of Discrete -Time Systems: Direct form of realisation; cascade and parallel forms.
Digital Filter Design: FIR and IIR design techniques; FFT and digital filter design technique; comparisons.
Discrete Fourier Transform: Theoretical development; discrete inverse Fourier transform; DFT and z-transform; DFT and digital filtering.
Fast Fourier Transform: Theoretical development; matrix formulation; signal flow graph; radix-2; DIT and DIF butterfly representations; windowing techniques.
Introduction to other Transforms: Hilbert transform; Walsh transform, FFT Signal Processing Applications: Spectral analysis; fast convolution; fast correlation; deconvolution; FFT signal detection.
Quantisation Effects in Digital Signal Processing: Fixed and floating point representation; rounding and truncation errors; quantisation of filter coefficients; quantisation effects in the computation of DFT.
Hardware Implementation of Digital Systems: Case Studies.
State Variable Representation of Digital Systems: Discrete state equations; transfer matrix of discreet systems.

Learning Outcomes

Subject-specific Knowledge

Design of FIR and IIR filters.
Design of spectral extraction algorithms.
Understanding of image processing and suitable.
2D and 3D transforms.

Subject-specific Skills

Key Skills

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Teaching by lectures and tutorials which are supported by a laboratory programme outside this module.
Written examinations are appropriate because of the wide range of in-depth, analytical material that is covered.
Theoretical coursework contributes a formative element to the module and aids the acquisition of subject-specific and key skills.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total Hours
Lectures	20	1 per week	1 hour	20
Tutorials	20	1 per week	1 hour	20
Preparation and Reading				101
Total				150

Summative Assessment

Component	Component Weighting	Element	Length/Duration	Element Weighting	Resit Opportunity
Examination	80%	Examination 2 hour written examination in may/june	2 hours	100%
Assignment	20%	Coursework		100%

Formative Assessment

One piece of coursework, which will be assessed but not included in the final average.

Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.