Module overview
The module aims to provide the foundations for biomedical engineers to be effective collaborators interdisciplinary research by being able to have the knowledge and understanding required to appraise and develop algorithmic solutions to real problems with resourcing constraints, such as time or space.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Select the most appropriate algorithm considering the constraints of a given problem
- Evaluate theoretically the complexity of algorithms
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Demonstrate the application of logical thinking in problem solving
- Estimate the performance of algorithms for a given dataset
- Select and apply algorithms appropriate to a simple biomedical engineering problem
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Demonstrate knowledge and understanding of the fundamentals of algorithms and data structures, including time and space complexity analysis.
- Demonstrate knowledge and understanding of the mathematical principles that underpin algorithms for biomedical engineering
Syllabus
1)Fundamental Maths
- Mathematical proof: by case analysis, by contradiction. Induction and recursion.
- Propositional logic. Predicate calculus. Soundness and completeness.
- Sets and relations.
- Graphs: (un)directed, (a)cyclic, (un)connected, and (un)weighted.
2)Algorithms and data representation
- Abstract Data Types (ADTs).
- Arrays.
- Linear and binary search.
- Sorting algorithms.
- Algorithmic analysis framework
* Average, best, and worst-case performance.
* Empirical and relative (order of growth) measurements: Constant,
logarithmic, linear, log linear, quadratic, cubic, and exponential.
* Time and space efficiency.
- Asymptotic complexity analysis: including Big O notation, little o, big Omega and big theta. Efficiency classes.
Learning and Teaching
Teaching and learning methods
In-person lectures and tutorials.
Individual study.
| Type | Hours |
|---|---|
| Preparation for scheduled sessions | 36 |
| Revision | 10 |
| Wider reading or practice | 68 |
| Lecture | 36 |
| Total study time | 150 |
Assessment
Assessment strategy
Invigilated closed-book written exam (100%)Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |