Overview
MATH5201 is an honours and postgraduate coursework Mathematics course. See the聽course overview聽below.
Units of credit:听6
笔谤别谤别辩耻颈蝉颈迟别蝉:听听(MATH2501 or MATH2601 or MATH2089 or MATH2099) and (MATH2011 or MATH2111 or MATH2018 (DN) or MATH2019 (DN) or MATH2069 (CR) or MATH2121 or MATH2221).
Cycle of offering:聽 Term 3 2023 (not offered every year)
Graduate attributes:聽The course will enhance your research, inquiry and analytical thinking abilities.
More information:聽聽The Course outline will be made available closer to the start of term - please visit this website: www.unsw.edu.au/course-outlines
Important additional information as of 2023
国产精品 Plagiarism Policy
The University requires all students to be aware of its聽.
For courses convened by the聽School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.
If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.
If you are currently enrolled in聽MATH5201, you can log into聽聽for this course.
Contact pg.mathsstats@unsw.edu.au for enquiries.
Course overview
A dynamical system is any system whose state changes as a function of time. Many nonlinear systems do not have explicit solutions. The dynamical systems approach shifts the focus from finding explicit solutions to discovering geometric properties of solutions. It also recognises that even a small amount of nonlinearity in a system can be responsible for very complicated chaotic behaviour. In this course you will learn the fundamentals of dynamical systems in discrete-time maps and continuous-time ODEs, allowing you to analyse the local and global behaviour of dynamical systems. You will also learn how to analyse time series data using nonlinear tools and build appropriate predictive models. This course is relevant for all majors Mathematics and related disciplines, and those interested in being able to model and understand dynamical phenomena (e.g. weather and climate, fluid dynamics, chemical dynamics, biological dynamics, and other physical and engineering processes).