Up to all Computation & Neural Sys(E&AS) Courses for 2016-17
Computation & Neural Sys(E&AS) (CNS) Graduate Courses (2016-17)
9 units (3-0-6):
Prerequisites: familiarity with digital circuits, probability theory, linear algebra, and differential equations. Programming will be required.
This course investigates computation by neurons. Of primary concern are models of neural computation and their neurological substrate, as well as the physics of collective computation. Thus, neurobiology is used as a motivating factor to introduce the relevant algorithms. Topics include rate-code neural networks, their differential equations, and equivalent circuits; stochastic models and their energy functions; associative memory; supervised and unsupervised learning; development; spike-based computing; single-cell computation; error and noise tolerance.
The online version of the Caltech Catalog is provided as a convenience; however, the printed version is the only
authoritative source of information about course offerings, option requirements, graduation requirements,
and other important topics.