Abstract
In this paper we present a new architecture for the representation of general fuzzy automata (GFA). It is based on second-order recurrent neural networks (2ORNN). The architecture implements the functions F/sub 1/ and F/sub 2/, used in GFA, into the structure of 2ORNN. The performance of this representation method is compared with a previous method for embedding fuzzy automata, and it is shown that GFA are more efficiently representable in 2ORNN.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
