ACS6128 Optimisation and Signal Processing

Module Description (subject to change)

This unit aims to provide detailed presentations to the use of the theory and methods of Optimisation and Signal Processing for a wide range of engineering problems. In the optimisation part, in additional to traditional optimisation methods, topics based on recent developments in heuristic methods, such as evolutionary computing (e.g. swarm intelligence) will also be presented. While in the signal processing part, the concepts of sampling, digital filters and digital image processing will be introduced; the analysis methods of discrete signals and systems in both the time and frequency domain, and basic digital image processing methods will be delivered.

Credits: 15 (Autumn semester)

Module Leader

Dr Leon Wei








Dr Leon Wei

Email: w.hualiang@sheffield.ac.uk
Amy Johnson Building

If you have any questions about the module please talk to me during the lectures or the labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask.

Outside of lectures please contact me via email, or drop in to see me.

Other Teaching Staff

Professor Zi-Qiang Lang
Email: z.lang@sheffield.ac.uk

Learning Outcomes

Learning Outcomes

At the end of the module, the student should be able to:

  • Explain the theory of commonly used optimisation methods, appraise and evaluate the strengths and limitations of these methods. [SM1fl, SM3fl, EA3fl, ET4fl]
  • Apply state-of-the-art classical and modern optimisation methods to solve engineering optimisation problems. [SM2fl, SM3fl D2fl]
  • Design and adapt different optimization methods and apply them to solve new problems within and outside engineering. [SM3fl, D2fl, EA3fl, ET4fl]
  • Explain basic digital signal analysis concepts, methods, and algorithms. [SM1fl, SM2fl]
  • Apply, design and analyse different types of digital filtering techniques. [EA1fl, D1fl, D2fl]
  • Design and implement appropriate methods for digital signal and digital image processing. [D1fl, D2fl]

This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage.

Syllabus

Syllabus 

  • TBC
Teaching Methods

Learning and Teaching Methods

NOTE: This summary of teaching methods is representative of a normal Semester. Owing to the ongoing disruption from Covid-19, the exact method of delivery will be different in 2020/21.

  • Lectures: 36 hours
  • Tutorials: 4 hours
  • Example classes: 4 hours
  • Lab Classes: 26 hours
  • Independent Study: 78 hours
Teaching Materials

Learning and Teaching Materials

All teaching materials will be available via MOLE.

Assessment

Assessment

  • 20% Coursework (Lab assignments)
  • 80% Coursework (Asynchronous, Limited Window)
Feedback

Feedback

Students will receive feedback through tutorials and question and answer sessions. They will also have the opportunity to undertake informal formative examinations e.g. laboratory exercises, for which they will receive feedback.

Student Evaluation

Student Evaluation

Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module.

You can view the latest Department response to the survey feedback here.

Recommended Reading

Recommended Reading

  • TBC