Digital Signal Analysis 4 (U00457)

? Credit Points : 10 ? SCQF Level : 10 ? Acronym : EEL-4-ELDSA

The aim of this course is to impart a knowledge and understanding of statistical analysis of signals and systems when considered in the time and frequency domains, and to enable the student to formally analyse systems through the use of spectral analysis and correlations. The student will also be able to take account of the effects of sampling in the time and frequency domain and understand how these affect the practical analysis procedures. The students will be able to select the appropriate infinite or finite impulse response digital filter and undertake the design of the filter coefficients. The student should gain a familiarity with the derivation of the fast Fourier transform (FFT) algorithm and with its computational advantages. An appreciation of simple sample rate changes and their effect on the filter design process would also be expected.

Entry Requirements

? Pre-requisites : Electronic Engineering 3, Maths 2 (TBA)

Subject Areas

Home subject area

Electronics, (School of Engineering and Electronics, Schedule M)

Delivery Information

? Normal year taken : 4th year

? Delivery Period : Semester 1 (Blocks 1-2)

? Contact Teaching Time : 3 hour(s) per week for 9 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
18/09/2007	09:00	09:50	Lecture Theatre 2, Hudson Beare Building	KB

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	09:00	09:50	KB
Tutorial	Wednesday	09:00	09:50	KB
Lecture	Friday	09:00	09:50	KB

Summary of Intended Learning Outcomes

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 and 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;
- select an appropriate analogue prototype and use the bilinear transformation method to obtain an IIR digital filter design;
- identify possible problems that can arise in IIR implementation and devise solutions to avoid or minimise their effects;
- explain the importance of linear phase filter design and apply window techniques to design a FIR filter;
- evaluate power spectral density at the output of a linear filter given the PSD at the input and perform a spectral factorisation on the output of a simple linear filter;
- recall how the discrete Fourier transform arises and recognise the effect of resolution and windowing functions upon the discrete Fourier transform;
- derive the structure of the fast Fourier transform from the equation of the discrete Fourier transform and distinguish between decimation-in-time, decimation-in-frequency, radix-2 FFT;
- analyse the effects of downsampling and upsampling on a signal and recognise the importance of decimation and interpolation filtering.