Introduces basic (artificial) neural network architectures and learning rules. Emphasizes mathematical analysis of these networks, methods of training them, and application to practical problems such as pattern recognition, signal processing, and control systems. Shows how to construct a network of "Neurons" and train them to serve a useful function. Prereqs., APPM 2360 or MATH 3130, and CSCI 1300 or equivalent. Same as ECEN 5120.