TY - GEN
T1 - Discrete fuzzy inference engine algorithm for digital implementations of approximate reasoning
AU - Zavala, Antonio H.
AU - Nieto, Oscar C.
AU - Batyrshin, Ildar
AU - Vargas, Luís V.
PY - 2008
Y1 - 2008
N2 - Fuzzy logic has become a very good choice to represent uncertain models of complex systems that cannot be easily represented in terms of conventional mathematics. Specifically fuzzy hardware has turned to be the choice to reach high speed inference rates. There are two forms to represent membership values universe: first one is when floating point numbers are used, second form is when integer universe is used. In the first case result of operations belongs to [0, 1], in the second case results belong to interval of integers [0, m], where m is an integer that can be represented by a different number of bits according to application resolution demands. This case is fully compatible with digital computers because floating point operations consume much more time and resources than integer operations. This paper presents an algorithm to implement fuzzy logic inference engine for discrete implementations and new method of defuzzification procedure, with the objective of reducing the number of instructions to be executed, having as consequence fewer processing time and less resources consumed. Simidation results for new methods are considered.
AB - Fuzzy logic has become a very good choice to represent uncertain models of complex systems that cannot be easily represented in terms of conventional mathematics. Specifically fuzzy hardware has turned to be the choice to reach high speed inference rates. There are two forms to represent membership values universe: first one is when floating point numbers are used, second form is when integer universe is used. In the first case result of operations belongs to [0, 1], in the second case results belong to interval of integers [0, m], where m is an integer that can be represented by a different number of bits according to application resolution demands. This case is fully compatible with digital computers because floating point operations consume much more time and resources than integer operations. This paper presents an algorithm to implement fuzzy logic inference engine for discrete implementations and new method of defuzzification procedure, with the objective of reducing the number of instructions to be executed, having as consequence fewer processing time and less resources consumed. Simidation results for new methods are considered.
UR - http://www.scopus.com/inward/record.url?scp=57849127620&partnerID=8YFLogxK
U2 - 10.1109/ICCIT.2008.375
DO - 10.1109/ICCIT.2008.375
M3 - Contribución a la conferencia
AN - SCOPUS:57849127620
SN - 9780769534077
T3 - Proceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008
SP - 696
EP - 703
BT - Proceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008
T2 - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008
Y2 - 11 November 2008 through 13 November 2008
ER -