Artificial Neural Networks

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Meeting Times and Place:

Thursdays  4:45 - 7:15 PM
Rowan Hall 239

Course Description:

Artificial neural networks covers the design of popular neural network architectures and their contemporary engineering applications. Neural network architectures that will be studied in detail include the multilayer perceptron, radial basis function and the Hopfield networks. State-of-the-art software will be used for network design. VLSI implementations of neural networks will be discussed. 

Semester Hours: 3

Prerequisites: Familiarity with Linear Algebra, Differential Equations and Multivariate Calculus. Consent of instructor.