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Course Descriptions

The physics curriculum is designed to develop a strong foundation in classical and modern physics, which will serve as a basis for future specialization, for additional study at the graduate level, and for design and development work in industrial laboratories. The curriculum emphasizes basic physical concepts, and includes extensive work in mathematics and related areas.

PH 538 - Introduction to Neural Networks

  • Credit Hours: 3R-3L-4C
  • Term Available: -
  • Prerequisites: Senior or Graduate Standing
  • Corequisites: None

Classifiers, linear separability. Supervised and unsupervised learning. Perceptrons. Back-propagation. Feedback networks. Hopfield networks. Associative memories. Fuzzy neural networks. Integral laboratory.