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Sampling theory for linear integral transforms

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Abstract

A sampling theorem is developed to reduce integration error in matrix–vector and linear multiplexing processors that perform discrete versions of continuous linear operations. By simply filtering the operation kernel before sampling, one can perform integration-error-free processing on inputs sampled at their Nyquist rate. Example applications to Laplace and Hilbert transformation are presented.

© 1981 Optical Society of America

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