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Semester 1

Digital Signal Analysis 4 (ELEE10010)

Subject

Electronics and Electronic Engineering

College

SCE

Credits

10

Normal Year Taken

4

Delivery Session Year

2022/2023

Pre-requisites

Course(s) covering Fourier transforms, linear systems and probability

Course Summary

Students will study the theory, and the practical application, of statistical analysis to signals and systems described by random processes. The topic will be approached from both time and frequency domains with an emphasis on studying the effect that analysis tools have on the resulting analysis. The course provides in-depth coverage of the discrete Fourier transform, and its role in spectrum estimation, as well as the design of finite impulse response filters, and their role in signal identification. In particular, issues such as resolution and dynamic range of an analysis system are dealt with, to give students an appreciation of how to apply the theory to engineering problems.

Course Description

Students will explore the analysis of practical signals through time and frequency analysis techniques, and understand the effect of each step in the process. After successful completion of this course a student should be able to: explain the relationships between and be able to manipulate time domain and frequency domain representations of signals; apply correlation techniques to an analytic or numerical problem, and relate the outcome to the statistical properties of the signal source(s); correctly define probability density functions and cumulative distribution functions, and be able to manipulate them to find moments of random variables and their sums; define the distinctions between wide-sense stationary, stationary, and ergodic processes, and be able to reason to which category a random process belongs; derive the power spectrum of a signal; define techniques for calculating moments in spectral and temporal domains; explain the importance of linear phase filter design and apply time and frequency techniques to design a FIR filter; evaluate power spectral density at the output of a linear filter given the PSD at the input; recognise the effect of resolution and windowing functions upon the discrete Fourier transform; analyse the effects of downsampling and upsampling on a signal and recognise the importance of decimation and interpolation filtering; explain the basis of matched filtering and be able to determine an appropriate filter for a given problem.

Assessment Information

Written Exam 0%, Coursework 100%, Practical Exam 0%

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