CISC 621 - Statistical Pattern Recognition

(3 semester hours)
Prerequisites: CISC 610, equivalent, or permission of the instructor
Description: Statistical pattern recognition techniques are used to design automated systems that improve their own performance through experience. This course covers the methodologies, technologies, and algorithms of statistical pattern recognition from a variety of perspectives. The objective is to provide a reasonable answer for all possible data and to classify input data in to objects or classes based on certain features. After taking the course, the student should have: a clear understanding of the design and construction and a pattern recognition system; major approaches in statistical and syntactic pattern recognition; some exposure to the theoretical issues involved in pattern recognition system design such as the curse of dimensionality and clear working knowledge of implementing pattern recognition techniques.