Foundations of Neural Networks (IME 877)
This course is designed to introduce students to the theory and practical applications of artificial neural networks. Neural networks are a broad class of computing mechanisms with active research in many disciplines including all fields of engineering, physics, psychology, biology, mathematics, medicine, business, economics, and computer science. Student will explore and investigate issues related to neural modeling through readings, lectures and hands-on projects. Course emphasis will be on the practical use neural networks for industrial problems such as pattern recognition, predictive and interpretive models, pattern classification, optimization and clustering. Application areas include quality control, economic forecasting, process monitoring and control, robotics control, economic analysis models, diagnostic models, combinatorial optimization and machine vision. Neural networks are not used as stand alone systems, but as components within larger systems such as expert, decision support, and on-line monitoring systems.