A WSTOLIC ARRAY FOR NONLINEAR ADAPTnrP, FILTERING AND PATTERN RECOGNITION

A systolic array for multi-dimensional fitting and interpolation using (nonlinear) radial basis functions is proposed. The fit may be constrained very simply to ensure that the resulting surface takes a pre-determined value at one or more specific points. The processor, which constitutes a form of nonlinear adaptive filter, behaves like a neural network based on the multi-layer, feed-forward perceptron model. One obvious application of such a network is as a pattern classifier, the constraints being used to ensure the correct classification of selected patterns.

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