Title :
Fuzzy logic, neural networks and virtual cognitive systems
Author_Institution :
Coll. of Eng., Saskatchewan Univ., Saskatoon, Sask., Canada
Abstract :
Several parallel advances have been made in the two distinct disciplines of fuzzy logic and neural networks. A single neuron can be viewed as a nonlinear mathematical operator or as a logical operator providing a mapping from many neural inputs. The theory of fuzzy logic is developed to capture the uncertainties associated with human cognitive processes. Fuzzy logic provides a mathematical strength to the emulation of certain perceptual and linguistic attributes associated with human cognition, whereas the science of neural networks provides new computing morphologies with learning and adaptive capabilities. An integration of these two fields: has the potential of generating a new discipline, `virtual intelligence´, with a new generation of computing systems, the `virtual cognitive systems´. The author explores the possibilities of such a new system. The system may recapture certain aspects of human cognition
Keywords :
cognitive systems; fuzzy logic; fuzzy neural nets; learning systems; uncertainty handling; virtual machines; adaptive capabilities; computing morphologies; fuzzy logic; human cognitive processes; learning; linguistic attributes; logical operator; neural inputs; neural networks; nonlinear mathematical operator; perceptual attributes; uncertainties; virtual cognitive systems; virtual intelligence; Biological neural networks; Biology computing; Cognition; Computer networks; Decision making; Fuzzy logic; Humans; Morphology; Neural networks; Neurons;
Conference_Titel :
Uncertainty Modeling and Analysis, 1993. Proceedings., Second International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-3850-8
DOI :
10.1109/ISUMA.1993.366785