Registry

Module Specifications

Archived Version 2005 - 2006

Module Title	Signals
Module Code	EE314
School	School of Electronic Engineering
Online Module Resources
Module Co-ordinator	Dr Ronan Scaife	Office Number	S355
Level	3	Credit Rating	10
Pre-requisite	EE203
Co-requisite	None

Module Aims

To provide the student with an understanding of modelling and analysis techniques for random and deterministic signals. To provide the student with an understanding of basic probability and random processes. To introduce students to analogue and digital modulation schemes.

Learning Outcomes

On completion of this module, the student will be able to Derive an expression for the frequency response of a LTI system. (PO1) State the Shannon-Whittaker Sampling Theorem. (PO1) Measure the frequency responses of filters and electro-acoustic systems. (PO2, PO5) Perform calculations using the Discrete Fourier Transform. (PO1) Apply Bayes Rule to calculation of error probabilities in binary symmetric channel. (PO1, PO2) Calculate the Autocorrelation Function of some random processes. (PO1, PO2) Use Wiener-Khinchine theorem to compute PSD from ACF. (PO1, PO2) Design a diode detector for AM signals. (PO3) Calculate the bandwidth needed for digital transmission of analogue signals.(PO2, PO3)

Indicative Time Allowances
	Hours
Lectures	60
Tutorials	12
Laboratories	18
Seminars	0
Independent Learning Time	60

Total	150
Placements
Assignments

NOTE

Assume that a 10 credit module load represents approximately 150 hours' work, which includes all teaching, in-course assignments, laboratory work or other specialised training and an estimated private learning time associated with the module.

Indicative Syllabus

Deterministic Signals Continuous Time Signals & Systems: The impulse function, convolution integral, convolution property of the Laplace transform, transfer functions, response of systems to complex exponential, review of Fourier Series, Fourier transform & convolution property. Discrete Time Signals and Systems: The unit sample function, convolution summation, convolution property of Z transform, Z transfer functions, simple filter designs. Sampling and Reconstruction: Sampling, Nyquist sampling theorem, frequency domain effects, reconstruction, the Bandlimited Interpolation Formula. Discrete Fourier Transform: Principles and simple applications; basics of FFT algorithms. Stochastic Signals: Stationarity and ergodicity, autocorrelation and power spectrum, Parseval's theorem, Wiener-Khintchine theorem, processing of random signals by linear systems, mean-square value of output. Probability and Random Processes Basic Probability: Set theory, Joint and Conditional Probability, Bayes' Theorem, Bernoulli Trials. Random Variables: Discrete and Continuous Random Variables, Distribution and Density Functions, Common Distributions and Densities, Functions of Random Variables, Multiple Random Variables. Random Processes: Deterministic and Nondeterministic Processes, Stationarity and Independence, Correlation Functions, Common Random Processes. Modulation Amplitude modulation, methods for modulation and detection, DSBSC modulation, coherent detection, squaring loop, SSB modulation and demodulation. Angle modulation, phase modulation, frequency modulation and detection. Sampling, quantization noise compansion, pulse code modulation. Bandpass digital communications; ASK, PSK.

Assessment
Continuous Assessment	20%	Examination Weight	80%

Indicative Reading List

Essential: M.L. Meade, C.R. Dillon, Signals and Systems (2/E), Chapman & Hall, 1991. Supplemental: Peyton Z. Peebles, Jr., Probability, Random Variables, and Random Signal Processing, McGraw-Hill,1993. A.B. Carlson, P.B. Crilly, J.C. Rutledge, Communication Systems (4/E), McGraw Hill, 2002. S. Haykin, Communications Systems.

Contribution to Programme Areas:

Science & Mathematics

Discipline - specific Technology

Information and Communications Technology

Design and Development

Engineering Practice

Social and Business Context

4

2

2

2

1

0

Contribution to Programme Outcomes:

Knowledge and Its Application:

The ability to derive and apply solutions from a knowledge of sciences, engineering sciences, technology and mathematics

Problem Solving:

The ability to identify, formulate, analyse and solve engineering problems;

Design:

The ability to design a system, component or process to meet specified needs, to design and conduct experiments and to analyse and interpret data;

Ethical Practice:

An understanding of the need for high ethical standards in the practice of engineering, including the responsibilities of the engineering profession towards people and the environment

Effective Work and Learning:

The ability to work effectively as an individual, in teams and in multidisciplinary settings together with the capacity to undertake lifelong learning;

Effective Communication:

The ability to communicate effectively with the engineering community and with society at large

3

3

3

0

1

0

Teaching & Learning Strategies/Assessment Methodology:

The module is delivered as lectures and a set of laboratory exercises.