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Complex Systems Related courses -- Winter 2008
The following are courses that are relevant to the study of complex
systems. These courses are not taught by CSCS, so inquiries should be
directed to the departments or instructors offering the courses.
This list is by no means complete. It just reflects the courses about
which we have been told. If you know of other relevant courses, please
let us know and we will announce them here. You can also find
information about other courses and research activities at UM by
following the various UM-related links at
our websites page.
Note well:
Some of these courses may be used to fullfill requirements for the
CSCS Graduate Certificate,
but only by permission of the CSCS Director. Please see the
CSCS Certificate Requirements for detailed
descriptions. For further information about using these courses to
fulfill CSCS requirements, please contact the CSCS office
( cscs at umich edu).
Psychology 703: Cogtnition and Environment
M/W 3:00-4:30PM. Instructor: Stephen Kaplan.
We consider the possibility that the environment makes a
major difference in whether people are reasonable or not, healthy or
not, fulfilled or not. That leads to examining what characterizes
environments that can have such profound impacts.
EECS 492: Introduction to Artificial Intelligence
T/TH 10:30-12:00. Instructor: Edmund Durfee. durfee@umich.edu
AE 551/EECS 562: Nonlinear Systems and Control
M/W 3:00-4:30PM. Instructor: N. Harris McClamroch. nhm@umich.edu
Topics:
Analysis of nonlinear dynamics
- phase plane dynamics
- fundamentals of odes: existence, uniqueness, and linearization
- input-output analysis of feedback systems: small gain theorem
- Liapunov methods for stability analysis
- applications of Liapunov methods: Lure problem
Nonlinear control
- control Liapunov functions and backstepping
- linearization by state feedback
Math 564: Special Topic in Mathematical Biology:
Modeling and Analysis of Biological Oscillators,
Thus, Thurs 10-11:30
Rm: 3088 East Hall
Instructor: Danny Foger
Background and Goals: From sleeping patterns, heartbeats, locomotion and
firefly flashing to the treatment of cancer, diabetes and neurological
disorders, oscillations are of great importance in biology and
medicine. Mathematical modeling and analysis are needed to understand
what causes these oscillations to emerge, properties of their period and
amplitude and how they synchronize to signals from other oscillators or
from the external world. The goal of this course will be to teach
students how to take real biological data, convert it to a system of
equations and simulate and/or analyze these equations.
Content: The course will provide an overview of biological
problems (including demonstrations) and modeling techniques. Models will
typically use ordinary differential equations. Mathematical techniques
introduced in this course include 1) the method of averaging 2) harmonic
balance 3) Fourier techniques 4) entrainment and coupling of oscillators
4) phase plane analysis and 5) various techniques from the theory of
dynamical systems. Emphasis will be placed on primary sources (papers
from the literature) particularly those in the biological sciences.
Consideration will be given in the problem sets and course project to
interdisciplinary student backgrounds. Teamwork will be encouraged.
Updated November 2007
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