Expert system on a chip: an engine for real-time approximate reasoning
ISMIS '86 Proceedings of the ACM SIGART international symposium on Methodologies for intelligent systems
Sugeno type controllers are universal controllers
Fuzzy Sets and Systems
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Computer architecture: single and parallel systems
Computer architecture: single and parallel systems
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Computer organization and design (2nd ed.): the hardware/software interface
Computer organization and design (2nd ed.): the hardware/software interface
A Fast Digital Fuzzy Processor
IEEE Micro
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing (The Handbooks of Fuzzy Sets)
VLSI implementation of a real time fuzzy processor
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
On fuzzy logic applications for automatic control, supervision, and fault diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
VLSI hardware architecture for complex fuzzy systems
IEEE Transactions on Fuzzy Systems
Fuzzy modeling based on generalized conjunction operations
IEEE Transactions on Fuzzy Systems
Hardware implementation of fuzzy flip-flops based on Łukasiewicz norms
ACACOS'10 Proceedings of the 9th WSEAS international conference on Applied computer and applied computational science
Conjunction and disjunction operations for digital fuzzy hardware
Applied Soft Computing
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Fuzzy theory applications have been explored and analyzed on fields as pattern recognition, control, data classification, signal processing, expert systems, among others. To accomplish this, more complex calculations and faster processing speed are required, turning fuzzy hardware implementation to be the perfect choice. Fuzzy operations as t-norms and t-conorms are used in fuzzy systems as conjunction and disjunction operations respectively. Commonly used t-norms for hardware implementation are minimum and algebraic product, first one is cheaper to implement; second consumes more resources. On this work FPGA technology is used to implement basic fuzzy t-norms as minimum, Lukasiewicz and drastic product into an 8 bit single circuit that allows operation selection. Timing, resources and comparative results are presented.