Abstract
The basic properties of nonlinear global filtering techniques are analyzed. A nonlinear processor for pattern recognition that is optimum in terms of discrimination and that is tolerant of variations of the object to be recognized is presented. We compare this processor with power-law and nonlinear joint transform correlators.
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