Abstract
The sparse distributed architecture described would be shown to function effectively as a fuzzy inference system giving essentially the same results as conventional techniques. However, whereas the conventional model reaches a glass ceiling as the order of target systems increases due to computer architectural limitations, this design is able to surpass this limit. It uses the same principles of max–min composition to solve inference problems, and comprises fuzzy sets that can encode a level of linguistic expression typical of such systems. It however expresses fuzzy sets differently, and performs the required computation in a manner suitable to the alternative representation. It may seem a rather complicated solution for low order problems (which it is) with the situation reversing itself for high order problems, the conventional solution being complicated if not impossible and the new architecture simple. The limitation, errors and performance of the new method when compared to the conventional method is documented and quantified by software written to model the two representations considered.
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Kong, A. Sparse distributed fuzzy inference systems. Soft Comput 10, 567–577 (2006). https://doi.org/10.1007/s00500-005-0518-4
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DOI: https://doi.org/10.1007/s00500-005-0518-4