Aims & Learning Objectives: The aims of this course are to introduce the basic concepts of analogue and digital signal processing and apply them to a range of examples.
After taking this unit the student should be able to:
* identify common noise sources and estimate their values in a given experiment;
* understand system responses, Laplace transforms, Z-transforms and transfer functions;
* understand the basics of digital and analogue signal processing;
* design digital and analogue filters with a desired frequency response;
* design and develop mathematical models for feedback systems and explain their advantages for measurement and control.
* apply signal processing techniques to a variety of electro-mechanical systems.
Content: Noise and random signals. Noise sources. AC measuring techniques and signal recovery methods. The Laplace transform and analogue signal processing, analogue filters. Sampled signals and the sampling theorem. Introduction to digital signal processing, z- transform. Frequency response. Design of digital filters using z- and Fourier transforms. Feedback, and its application to measurement and control systems. Static and dynamic theory of feedback.
Modelling of physical systems. Case studies in the applications of analogue and digital signal analysis. Examples chosen from, for example, vibrating systems, fluid dynamics, speech recognition and synthesis, and image processing.
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