Course Title
Neural Networks
Department
Credit Hrs
3
Grade Modes
Audit, Pass/Fail, Standard Letter
Course Description
Biological neurons and their modeling. An overview of single/multilayer feedforward/back ANN models and learning rules, single layer perceptron model, multi-layer feedforward error backpropagation, recurrent associative memory, Hopfield model, multilayer ANNs for clustering & competitive learning, Hamming/Max, un/supervised learning, Kohonen SOFM, Learning Vector Quantization, counter propagation ANN model, Adaptive Resonance Theory model. ANNs applications (projects).
Prerequisite
Complete ALL of the following Courses:
- MATH2420
- MATH3082
AND MATH3082L
Complete ALL of the following Courses:
- CSE3007
OR xFmCNrqwdeCn9Hlclc1i
The Math and Computer Science Requirement courses must be passed with a C or better or consent of instructor and advisor before enrolling in CSE 4065.