This book delivers theoretical and practical knowledge for
developing algorithms that infer linear and non-linear multivariate
models, providing a methodology for inductive learning of
polynomial neural network models (PNN) from data. The text
emphasizes an organized model identification process by which to
discover models that generalize and predict well. The book further
facilitates the discovery of polynomial models for time-series
prediction.
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