Winter 2005 One Page FlyerSySc 514: System DynamicsTu 6-9:30PM, SB2 469
A lab and web-based course that introduces the student to the study of the dynamic behavior of continuous systems containing feedback. Vensim is the primary simulation language used in the course. "Lecture" materials are provided on the web using WebCT. Class time is used to assist students in carrying out various labs the reinforce the primary concepts. Some students may find that they can take the course almost entirely remotely. More information: http://www.webct.pdx.edu/public/sysc514ww2/index.html SySc 551/651: Discrete Multivariate ModelingMW 4:00-5:50, SB2 104
The course focuses on information theory as a modeling framework and as a tool for discrete multivariate analysis. The course presents set- and information-theoretic methods for studying static or dynamic (time series) relations among qualitative variables or among quantitative variables having unknown nonlinear relationships. In the "general systems" literature, this is known as "reconstructability analysis" (RA). RA overlaps partially with log-linear statistical techniques widely used in the social sciences; both are especially valuable in data-rich applications (but RA is not exclusively statistical). RA is highly relevant to the many interrelated "projects" which go under the names of data-mining, machine learning, knowledge discovery and representation, etc. Applied to data analysis, RA allows the decomposition and compression of multivariate probability distributions (contingency tables) and set-theoretic relations (and mappings), as well as the composition of multiple distributions/relations. The methods are very general. They are valuable in the natural and social sciences and in engineering, business, or other professional fields whenever categorical variables are useful or linear models are inadequate. Applied to the conceptualization of "structure" and "complexity," these set- and information-theoretic ideas are foundational for systems science. See also Research in Discrete Multivariate Modeling SySc 576 AI: Neural Networks IIMW 4:00-5:50, Room TBA
Focuses on applications. Topics in fuzzy set theory, control theory, and pattern recognition are studied and incorporated in considering neural networks. A Design project (using NN simulator) in selected application area is done by each student. For more information, see the course home page for Winter 2005. |
