Title :
Fuzzy hypercubes: a possibilistic inferencing paradigm
Author :
Kang, Hoon ; Vachtsevanos, George
Author_Institution :
Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
A robust and reliable learning and reasoning mechanism is addressed based upon fuzzy set theory and fuzzy associative memories. The mechanism stores an initial knowledge base via approximate learning and utilizes this information for decision-making systems via fuzzy inferencing. This fuzzy computer architecture, a fuzzy hypercube, processes all the rules in one clock period in parallel. Fuzzy hypercubes can be applied to control of a class of complex and highly nonlinear systems which suffer from vagueness or uncertainty
Keywords :
content-addressable storage; fuzzy logic; hypercube networks; inference mechanisms; learning (artificial intelligence); approximate learning; complex system control; decision-making systems; fuzzy associative memories; fuzzy hypercube; fuzzy inferencing; fuzzy set theory; highly nonlinear system control; initial knowledge base; possibilistic inferencing paradigm; reasoning mechanism; robust reliable learning mechanism; uncertainty; vagueness; Associative memory; Clocks; Computer architecture; Decision making; Fuzzy reasoning; Fuzzy set theory; Fuzzy systems; Hypercubes; Reliability theory; Robustness;
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
DOI :
10.1109/FUZZY.1992.258701
