Advanced Digital Signal Processing (102H6)
Advanced Digital Signal Processing
Module 102H6
Module details for 2023/24.
15 credits
FHEQ Level 7 (Masters)
Module Outline
The module covers the theory and applications of digital signal processing.
The module starts with the revision of linear systems theory, discretisation, Fourier, Laplace, and z-transforms. The relationship between s and z planes, stability, poles and zero locations are examined.
This is followed by a detailed discussion of the system response, convolution and correlation functions. Design methods for finite impulse response (FIR) and infinite impulse response (IIR) digital filters are covered in detail.
The discrete and fast Fourier transform algorithm are covered in detail.
Two-dimensional filtering for image and video processing are examined along with the discrete cosine transforms for image compression.
The lectures are supported by laboratory sessions in which the filtering techniques are implemented on DSP hardware, coding in both C and Matlab.
The syllabus covers the following AHEP4 learning outcomes: M1, M2, M3, M4, M12
Library
P. Lynn, W. Fuerst, "Introductory Digital Signal Processing", Wiley, 1994.
E. Ifeachor, B. Jervis, "Digital Signal Processing, A Practical Approach", Addison Wesley, 1996.
J. Proakis, D. Manolakis, "Digital Signal processing", Prentics Hall, 1996
S. Mitra, "Digital Signal Processing ", McGraw-Hill, 2006
E. Brigham, "The Fast Fourier Transform and its Applications", Prentice-Hall, 1988
Module learning outcomes
Be capable of analysing a system response in both the time and frequency domains. Understanding of convolution and correlation.
Be capable of the design from a given specification of finite impulse response and infinite impulse response filters.
Understanding of the relationship between the continuous and discrete Fourier transforms; the fast Fourier transform.
Be able to extend digital analysis to multi-dimensional signals such as images.
Type | Timing | Weighting |
---|---|---|
Coursework | 25.00% | |
Coursework components. Weighted as shown below. | ||
Software Exercise | T1 Week 11 | 100.00% |
Unseen Examination | Semester 1 Assessment | 75.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
Term | Method | Duration | Week pattern |
---|---|---|---|
Autumn Semester | Lecture | 2 hours | 11111111111 |
Autumn Semester | Laboratory | 2 hours | 00111111110 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr William Wang
Assess convenor
/profiles/101946
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