Year 4 Spring EE Modules
Spring Term
ELEC97002 – Adaptive Signal Processing and Machine Intelligence
Very similar in style to the third year ASP course. – Emilie d’Olne, 2019/20
ELEC97010 – Analogue Signal Processing
Interesting modules that really follows from biomedical electronics. The material is quite dense but the exam always has the same format – Clementine Biet, 2019/20
ELEC97023 – Digital Signal Processing and Digital Filters
This was Dr Bhandari's first year teaching the course, I get the impression he may change it considerably for next year. The exam was completely different to previous years, and much more difficult. I would recommend only taking this if you really really like DSP. Nothing ground-breaking compared to the 3rd year course is introduced, and I really wouldn't take this module unless you need it. – 19/20
This was the first year that Dr Bhandari was teaching this module, so it may change a lot next year. The slides were still Mike Brookes', but Bhandari had a few extra slides here and there to put emphasis on different things, a bit hard to follow sometimes. Quite important to attend the
lectures, because the sound was rarely recorded on panopto, and a lot of the exam was about things covered in class but not in the notes. – Emilie d’Olne, 2019/20
ELEC97025 – Discrete-Event Systems
This module is confusing at first but if you spend time understanding the algorithms, you'll realise it's pretty logical. You don't need to have taken control modules in 3rd year or even in autumn term of 4th year to do well in this module. There is not too many resources online that use the same terminology as this module, but there is a textbook and Angeli's notes, and those combined are more than enough to understand what is going on. The coursework is a bit of a shock to the system but once you work it out, it is easy to do well in both the coursework and the exam. – 19/20
ELEC97027 – Digital Control Systems
ELEC97048 – Information Theory
ELEC97041 – High Performance Analogue Electronics
The lecture notes are not available online and the lectures are not recorded so it is quite difficult to catch up on the material or to understand prior to the lectures. The content is quite challenging as it requires a great knowledge of semiconductors. – Clementine Biet, 2019/20
ELEC97055 – MEMS and Nanotechnology
ELEC97066 – Power System Dynamics, Stability and Control
ELEC97070 – Predictive Control
ELEC97074 – Radio Frequency Electronics
ELEC97079 – Speech Processing
If you liked third year DSP, you'll like this. Very interesting to cover speech in details, which is rarely done in broader signal processing courses. – Emilie d’Olne, 2019/20
good lectures but hard examination – 19/20
ELEC97083 – Sustainable Electrical Systems
Super interesting module that highlights the options for sustainable energy generation in the past, currently and the plans for the future, as well as reasons for limitations etc. They bring in guest lecturers so you know that the content is topical and up to date. Both courseworks are not only interesting, but simple to do and easy to get a good mark. The same can be said for the exam if you know the content well. – 19/20
ELEC97090 – Traffic Theory & Queueing Systems
ELEC97092 – Wavelets, Representation Learning and their Applications
Probably the best course I took at Imperial. Most of the concepts covered are somewhat new, and honestly quite challenging, but Dragotti gives a refresher on all the maths you need, and does a very good job at giving you intuition on everything. In the end you'll learn about super interesting principles behind data representation and compression. There is a small coursework component to this module - it is very quick to do and helps a lot by giving practical applications of what you're studying. The exam is not too hard compared to the module itself. – Emilie d’Olne, 2019/20
a hard course, but can learn something from it; everything is well-structured – 19/20
ELEC97094 – Wireless Communications
ELEC97100 – Signal Processing and Machine Learning for Finance
ELEC97109 – Design of Linear Multivariable Control Systems
ELEC97112 – Computer Vision and Pattern Recognition
Pattern Recognition: Really interesting module that gives you an insight into the low level principles of machine learning for face recognition, actually implementing the techniques rather than using standard libraries. You can take this module and do well without having taken any ML related modules previously, but a good working knowledge of python is helpful. The lectures may seem confusing at first and the coursework is definitely hard, but once you get through it you finish the module with a good solid understanding of what you did. – 19/20
Pattern Recognition: learns fundamental machine learning algorithms (pca, lda, metric learning); high marks are given – 19/20