1. Demonstrate a critical understanding of analogue and digital signal representation and processing techniques. AHEP 4: F2, F3, F12, F13, F15.
2. Apply appropriate analytical techniques to critically evaluate signals and their processing. AHEP 4: F3, F12, F13.
3. Use simulation software with key analytical skills and understanding to evaluate theoretical concepts. AHEP 4: F3, F12, F13.
4. Communicate ideas effectively. AHEP 4: F17.

A 1.5-hour online examination weighted at 50% which will assess Learning Outcomes 1 and 2. Meeting AHEP 4 Outcomes F2, F3, F12, F13, F15.

Coursework (approx. 2000 words) weighted at 50% which will assess Learning Outcomes 3 and 4. Meeting AHEP 4 Outcomes F3, F12, F13, F17.

Signals and Systems Overview
Signal Classifications: continuous time and discrete time signals, deterministic and non-deterministic signals, periodic and aperiodic signals, causal and non-causal signals, energy and power signals.
Signal Basic Types: unit step function, unit impulse function, ramp signal, parabolic signal, exponential signal.
Signal parameters, average, root mean square, mean square, normalised average power.
Signal representation: time-domain, frequency domain, continuous-time, discrete-time.
Trigonometric and exponential form, phasors, Argand diagram representation.
Elementary operations on signals: time shifting, time scaling, time reversal.
Fourier series, spectra of common signals. Fourier Transforms.
System Classification: continuous and discrete time systems, linear and non-linear systems, time invariant and time varying systems, causal and non-causal systems, stable and unstable systems.
Sampling Theorem and analogue-to-digital conversion. Quantisation error and signal-to-quantisation noise.
Impulse response of Linear Time Invariant systems.
Finite and Infinite impulse response systems.
Correlation and Convolution.
Applications of signal processing.

Nowadays signals are encountered extensively in our day-to-day lives such as while making a phone call, listening to music, sharing audio files, speech recognitions systems; Siri, Google now etc. Not only these but signals are also crucial while performing medical diagnostics such as EEGs, ECGs, and X-Ray images. Each of these involve obtaining, storing, transmitting, and processing of information from real world. This module is intended to equip students with foundational knowledge and practice in signals and systems which is essential for engineering studies.

Several methods of representation of a signal, various classifications of signals and the analysis tools are studied. Signal processing techniques such as correlation and convolution are practiced and their practical applications in real-world systems are discussed.

This module aims to develop your skills and knowledge as a remote/off-campus student. Learning about all aspects of the content will be facilitated via a VLE (Virtual Learning Environment). Subsequently, students will work through the module material provided on the VLE at a pace suggested within the VLE for the module. The material will include activities that will allow students to assimilate the concepts and skills required by the module. In addition, students will be encouraged to discuss relevant aspects via vehicles such as discussion forums hosted within the VLE, which will allow discussion with the peers as well as module tutor. Live tutorials, other materials, and meetings will occur as appropriate to provide additional support.

Rao, K.D. and Tunga, S., (2018). Signals and systems. Birkhäuser. ISBN: 978-3-319-68675-2
Chaparro, L. and Akan, A., (2018). Signals and Systems using MATLAB. 3rd edn. Academic Press. ISBN: 978-0-128-14205-9
Sundararajan, D., (2009). A practical approach to signals and systems. John Wiley & Sons. ISBN: 978-0-470-82354-5
Ingle V. K. and Proakis J. G., (2007), Digital Signal Processing Using MATLAB, 2nd edn. Cengage Learning, ISBN: 978-0-495-07311-6
Andreas A., (2006), Digital Signal Processing: Signals, Systems and Filters, McGraw-Hill, ISBN: 978-0-071-45424-7

Blackboard VLE.
Online library facilities
Google Scholar.
Simulation Software packages: MATLAB
Students will need to ensure they have access to a computer and reliable internet connection.