Mendel In many practical signal processing problems, information is often represented in two forms: one is a set of input-output data pairs, obtained by measuring the outputs of the system for some typical input signals; and, the other is a set of linguistic descriptions about the system, often in the form of IF-THEN fuzzy rules, from human experts who are very familiar with the behavior of the system. This research is developing a general method to combine both numerical input/output pairs and linguistic IF-THEN rules into signal processing system design within the framework of fuzzy system theory. The objectives are to: 1. theoretically justify the practical successes of fuzzy systems; 2. develop synthesis methods for fuzzy systems which use both numerical and linguistic information; and 3. apply these synthesis methods to signal processing problems, such as time-series prediction, and subject these methods to theoretical performance analyses. An optimal design method for fuzzy systems which will match given input-output pairs to arbitrary accuracy is also being developed.
