Mathematics

Overview

1. Periodic functions, Fourier series and Fourier coefficients.
2. Vector/matrix notations and operations.
3. Fundamental theorem of linear systems, solving linear systems.
4. Orthogonality, eigenvalues, eigenvectors, eigendecomposition, and QR decomposition.
5. Multivariate functions, partial derivatives, chain rule.
6. Multivariate integration.
7. Multivariate optimisation: unconstrained optimisation and constrained optimisation.
8. Basic Probability Concepts and Common Probability Distributions.
9. Sampling, Parameter Estimation, Statistical Inference.

Learning Objectives

Learning Outcomes
Fundamental understanding of the modern engineering mathematics, probability and statistics, basic theoretical concepts, methods, with application to the problems of analysis and modelling in electronic communications, microwave engineering and design of electronic components, circuits and systems.

Understand basic probability concepts, expectation and some of the most common probability distributions encountered in engineering. Understand different concepts related to sampling and data analysis. Build an appreciation of some of the different types of parameter estimation. Develop an understanding of the principles of statistical inference including hypothesis testing.

Skills

Skills
• Matrix algebra, analysis and modelling of linear systems.
• Fourier analysis
• Optimisation theory
• Multivariate calculus
• Probability and statistical inference
• Computational statistics.

Assessment

No compulsory element