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Practical Constraints Pertinent To The Design Of Neural Networks, Said Sadek Abdallah, Rufus H. Cofer
Practical Constraints Pertinent To The Design Of Neural Networks, Said Sadek Abdallah, Rufus H. Cofer
Electrical Engineering and Computer Science Faculty Publications
in designing a feedforward neural network for numerical computation using the backpropagation algorithm it is essential to know that the resulting network has a practical global minimum, meaning that convergence to a stationary solution can be achieved in reasonable time and using a network of reasonable size. This is in contrast to theoretical results indicating that any square-integrable (L2) function can be computed assuming that an unlimited number of neurons are available. A class of problems is discussed that does not fit into this category. Although these problems are conceptually simple, it is shown that in practice convergence to a …