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Backpropagation


Introduction
An introduction to the chapter, including information on additional resources
Architecture
A discussion of the architecture, simulation, and training of backpropagation networks
Faster Training
A discussion of several high-performance backpropagation training algorithms
Speed and Memory Comparison
A comparison of the memory and speed of different backpropagation training algorithms
Improving Generalization
A discussion of two methods for improving generalization of a network -- early stopping and regularization
Preprocessing and Postprocessing
A discussion of preprocessing routines that can be used to make training more efficient, along with techniques to measure the performance of a trained network
Sample Training Session
A tutorial consisting of a sample training session that demonstrates many of the chapter concepts
Limitations and Cautions
A discussion of limitations and cautions to consider when creating and training perceptron networks


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