Abstract
Feature extraction is a widely used technique in the field of image processing. This paper shows that 2D nonlinear feature extraction is also useful in controllers that are based on artificial intelligence techniques. It can, for example, be used to limit the knowledge explosion problem encountered when online sensors interact with expert systems. The feature extraction scheme suggested uses nonlinear hybrid median filters, is noise tolerant, non-model-dependent, preserves discontinuities, and is capable of a 90% reduction in information representation with negligible signal feature loss.
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