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Digital Signal Processing
Lecturer: Dr M.G. Kuhn
No. of lectures: 8
Prerequisite courses: Continuous Mathematics, Numerical Analysis I, Probability
Some of the material covered in Digital Communication I and
Information Theory and Coding will also help in this course.
Aims
This course teaches the basic signal processing principles necessary
to understand many modern high-tech systems. Students will gain
practical experience from numerical experiments in MATLAB-based
programming assignments.
Lectures
- MATLAB.
Use of MATLAB on PWF machines to perform numerical experiments and
visualise the results in homework exercises.
- Signals and systems.
Review of complex numbers, decibels, harmonic functions and phasors,
amplitude, phase, power, Fourier transform, convolution,
time-invariant linear systems, commutativity, examples from
electronics, optics and acoustics.
- Discrete sequences.
Dirac delta function, aliasing, periodic sampling of low-pass and
band-pass signals, spectral inversion, quantisation.
- Discrete Fourier transform.
Continuous versus discrete Fourier transform, symmetry, linearity,
review of FFT, spectral estimation, windowing, periodogram.
- Filters.
Finite and infinite impulse response filters, implementation forms,
polynomial representation, z-transform, filter design techniques,
FFT-based convolution and FIR filtering.
- Modulation.
Overview of analog and digital modulation techniques (AM, SSB, FSK,
QAM), channel properties, noise, modem design examples and
experiments.
- Various techniques and examples.
Deconvolution of blurred signals, Wiener filter, resampling and time
warping, correlation and averaging, detection of weak signals in
noise, some audio effects.
Objectives
By the end of the course students should
- be able to apply basic properties of
time-invariant linear systems
- understand sampling, aliasing, convolution,
filtering, the pitfalls of spectral estimation
- be able to explain the above in time and frequency domain
representations
- be competent to use filter-design software
- be able to visualise and discuss digital filters in the z-domain
- be able to use the FFT for convolution, deconvolution, filtering
- be able to implement, apply and evaluate simple
DSP applications in MATLAB
- have gained practical experience in designing
digital communication and audio processing algorithms
Recommended books
* Lyons, R.G. (2001). Understanding digital signal processing.
Prentice-Hall.
Stein, J. (2000). Digital signal processing - a computer science
perspective. Wiley.
Smith, S.W. (2003). Digital signal processing - a practical guide for
engineers and scientists. Newness.
Steiglitz, K. (1996). A digital signal processing primer - with
applications to digital audio and computer music. Addison-Wesley.
Oppenheim, A.V. & Schafer R.W. (1999). Discrete-time digital signal
processing. Prentice-Hall (2nd ed.).
Next: Distributed Systems
Up: Easter Term 2004: Part
Previous: Business Studies
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Christine Northeast
Thu Sep 4 15:29:01 BST 2003