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Function Approximation, Clustering, and Control

Perform regression, classification, clustering, and model nonlinear dynamic systems using shallow neural networks

Generalize nonlinear relationships between example inputs and outputs, perform unsupervised learning with clustering and autoencoders.

Dynamic neural networks including NARX and Time-Delay; create Simulink models; control nonlinear systems using model-predictive, NARMA-L2, and model-reference neural networks.