Lattice-valued logic and neural networks

Author

Liu, Yunfeng ; Wang, P.K.C.

Author_Institution

Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA

fYear

1997

fDate

21-24 Sep 1997

Firstpage

350

Lastpage

355

Abstract

Lattice-valued logic is a generalized logic whose definition function is set-valued. It can be applied to switching systems by defining a lattice-valued switch (LVS) whose parallel connection “∪” and cascade connection “∩” are generalized operators which may correspond respectively to the “max” (v) and “min” (∧) operators in fuzzy logic, or “+” and “·” operators in neural networks. Here, it is shown that both fuzzy logic based systems (FLS) and neural network based systems (NNS) can have a unified representation in the form of LVS. A fuzzy Boolean switching system which has the advantages of both FLS and NNS is introduced along with a method for its design

Keywords

Boolean algebra; fuzzy logic; fuzzy neural nets; switching functions; FLS; LVS; NNS; cascade connection; fuzzy Boolean switching system; fuzzy logic based systems; lattice-valued logic; lattice-valued switch; neural networks; parallel connection; set-valued function; switching systems; Boolean algebra; Design methodology; Expert systems; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Hybrid intelligent systems; Neural networks; Switches; Switching systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American

Conference_Location

Syracuse, NY

Print_ISBN

0-7803-4078-7

Type

conf

DOI

10.1109/NAFIPS.1997.624065

Filename

624065