Introduction to signals and signal analysis. Frequency and time domain representations of signals. A review of the Fourier Series, Fourier Transform and Laplace Transforms. Noise: definitions and sources of noise in signal analysis.
Digital Signal Processing:
The sampling theorem, Aliasing, Anti-Aliasing and Anti-Imaging Filters, ADCs and DACs. The Fourier Transform (FT). The Discrete Fourier Transform (DFT) and The Fast Fourier Transform (FFT).The Z-transform. Pole-Zero placement methods for signal analysis. Transfer functions in S and Z domains. Theory, design and performance of Finite Impulse-Response (FIR) and Infinite-Impulse-Response (IIR) Filters. Multirate DSP. Architectures and devices for digital signal processing. Effects of Finite Precision.
Applications of DSP:
Processing and filtering of signals for Instrumentation and measurement, Processing and filtering of images: DSP in modern communication systems.
This module appears in:
Total contact hours: 62
Private study hours: 88
Total study hours: 150
Method of assessment
1 Understand the principles of Digital Signals in both the time and frequency domains and use the Fourier Transform, the Fast Fourier Transform and the Z-Transform to analyse such signals.
2 Understand and critically appraise the effects of noise on digital systems;
3 Employ standard methods to design filters for use in processing digital signals.
4 Comprehensively understand how DSP techniques can be used in Instrumentation and Measurement, image processing (and image compression) and modern communication systems.