Fuzzy neural networks and cognitive modeling

Over the last two decades or so, several significant advances have been mad e in two distinct fields: neural networks and fuzzy systems. The theory of fuzzy systems provides a mathematical framework for capturing the uncertain ties associated with human cognitive processes, such as thinking and reason ing, and for emulating corresponding perceptual and control processes. The paradigms of neural networks offer the complementary attributes of learning and adaptation, together with the innate efficiency of parallel operation. In this paper we explore fuzzy neural networks, the product of fusion of ne ural networks and fuzzy mathematics, which have potential for combining the se mathematical tools into a single capsule. For their favorable properties , the fuzzy neural networks could be used in the development of systems wit h some sort of cognitive abilities. These cognitive systems would have the potential to recapitulate certain aspects of human cognition such as percep tion, memory, learning, and decision making.