ENEE 4320 - Artificial Neural Network Design

(3) Credit Hours

Introduction to fundamental neural network architectures and learning rules. Supervised and unsupervised learning of feedforward and recurrent associative memory networks, perceptron layers, associative and competitive networks. Application to practical engineering problems in the areas of classification, pattern recognition, function approximation and control systems such as design of neuro-controllers. Implementation issues. Spring semester. Lecture 3 hours. Prerequisites: ENEE 2250 or CPSC 1110, MATH 2560 or department head approval. Differential Course Fee will be assessed.