Biological Cybernetics: Non-Linear systems

• 2021 notes are available at (http://www.cybernetia.co.uk/teaching/biocybernetics/)
• 2020 notes are available at (http://www.personal.reading.ac.uk/~shshawin/teaching/biocybernetics/)

Outline

• Definition of linear and non-linear systems. System states.
• Ordinary differential equations and state systems
• Numerial integration
• Linearisation around an operating point
• Phase space, stable nodes, unstable nodes, saddle points
• Pendulum equations
• Optimization
• Machine intelligence
• Classification and confusion

• Neural networks.
• Learning and adaptive systems (back propagation)

There may be additional information on the websites

• (http://www.personal.reading.ac.uk/~shshawin/teaching/biocybernetics/01intro.html)

Assessment

Assessment is via examination and one assignment (to be posted on blackboard)

The assignment will be set in December with a submission in January

Labs and interactive sessions

Autumn labs on Mon 08-11-2021 and Mon 22-11-2021

Drop in/interactive sessions on Tuesdays at 17:00 (t.b.d. but probably on MS teams)

• Tutorials

• Matlab: Numerical integration, time domain and phase plane plots
• Matlab: Optimization
• Matlab: Machine learning and classification
• Matlab: Learning by back propogation and neural networks

Books:

The following books are some of the references used in the course

Assumed background knowledge

• algebra, laws of association, commutation and distribution
• matrices addition, multiplication, inverse,
• differentiation, integration and Laplace transforms