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.).