Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
VHDL and fuzzy logic if-then rules
EURO-DAC '92 Proceedings of the conference on European design automation
VHDL package for description of fuzzy logic controllers
EURO-DAC '95/EURO-VHDL '95 Proceedings of the conference on European design automation
Microelectronic design of fuzzy logic-based systems
Microelectronic design of fuzzy logic-based systems
XFVHDL: a tool for the synthesis of fuzzy logic controllers
Proceedings of the conference on Design, automation and test in Europe
Prototyping of Fuzzy Logic-Based Controllers Using Standard FPGA Development Boards
RSP '02 Proceedings of the 13th IEEE International Workshop on Rapid System Prototyping (RSP'02)
Computer-aided design of fuzzy systems based on generic VHDL specifications
IEEE Transactions on Fuzzy Systems
Fuzzy logic activities at the microelectronics institute of seville
WIRN'05 Proceedings of the 16th Italian conference on Neural Nets
Implementation of fuzzy logic controller in FPGA circuit for guiding electric wheelchair
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Particle swarm optimization of interval type-2 fuzzy systems for FPGA applications
Applied Soft Computing
A multi-context processor for real-time concurrent tasks fuzzy reasoning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The number of electronic applications using fuzzy logic-based solutions has increased considerably in the last few years. Concurrently, new CAD tools that explore different implementation technologies for this type of systems have been developed. In this paper we illustrate a fuzzy logic system design strategy based on a high level description. Employing this high level description, the knowledge base is translated to a format in appearance close to the natural language with the particularity that it uses a hardware description language (VHDL) directly synthesizable on an FPGA circuit. In addition, we analyze different approaches for FPGA implementations of fuzzy systems in order to characterize them in terms of area and speed. Among them, the use of specific processing architectures implemented on FPGAs presents as main advantages a good ''cost-performance'' ratio and an acceptably short development time. The different synthesis facilities provided by the Xfuzzy design environment for the implementation of programmable fuzzy systems, which take advantage of the available resources in the current FPGA families, are also analyzed in this paper.