Ponce-Cruz, Pedro.
Fuzzy Logic Type 1 and Type 2 Based on LabVIEW™ FPGA [electronic resource] / by Pedro Ponce-Cruz, Arturo Molina, Brian MacCleery. - 1st ed. 2016. - XVI, 233 p. 203 illus., 52 illus. in color. online resource. - Studies in Fuzziness and Soft Computing, 334 1860-0808 ; . - Studies in Fuzziness and Soft Computing, 334 .
Literature Review for Digital Implementations of Fuzzy Logic Type 1 and Type 2 -- LABVIEW™ FPGA -- Real-Time Fuzzy-Logic Controllers -- Fuzzy Logic Type 1 and Type 2 LABVIEW™ FPGA Toolkit.
This book is a comprehensive introduction to LabVIEW FPGA™, a package allowing the programming of intelligent digital controllers in field programmable gate arrays (FPGAs) using graphical code. It shows how both potential difficulties with understanding and programming in VHDL and the consequent difficulty and slowness of implementation can be sidestepped. The text includes a clear theoretical explanation of fuzzy logic (type 1 and type 2) with case studies that implement the theory and systematically demonstrate the implementation process. It goes on to describe basic and advanced levels of programming LabVIEW FPGA and show how implementation of fuzzy-logic control in FPGAs improves system responses. A complete toolkit for implementing fuzzy controllers in LabVIEW FPGA has been developed with the book so that readers can generate new fuzzy controllers and deploy them immediately. Problems and their solutions allow readers to practice the techniques and to absorb the theoretical ideas as they arise. Fuzzy Logic Type 1 and Type 2 Based on LabVIEW FPGA™, helps students studying embedded control systems to design and program those controllers more efficiently and to understand the benefits of using fuzzy logic in doing so. Researchers working with FPGAs find the text useful as an introduction to LabVIEW and as a tool helping them design embedded systems.
9783319266565
10.1007/978-3-319-26656-5 doi
Computational intelligence.
Electronic circuits.
Artificial intelligence.
Computational Intelligence.
Electronic Circuits and Systems.
Artificial Intelligence.
Q342
006.3
Fuzzy Logic Type 1 and Type 2 Based on LabVIEW™ FPGA [electronic resource] / by Pedro Ponce-Cruz, Arturo Molina, Brian MacCleery. - 1st ed. 2016. - XVI, 233 p. 203 illus., 52 illus. in color. online resource. - Studies in Fuzziness and Soft Computing, 334 1860-0808 ; . - Studies in Fuzziness and Soft Computing, 334 .
Literature Review for Digital Implementations of Fuzzy Logic Type 1 and Type 2 -- LABVIEW™ FPGA -- Real-Time Fuzzy-Logic Controllers -- Fuzzy Logic Type 1 and Type 2 LABVIEW™ FPGA Toolkit.
This book is a comprehensive introduction to LabVIEW FPGA™, a package allowing the programming of intelligent digital controllers in field programmable gate arrays (FPGAs) using graphical code. It shows how both potential difficulties with understanding and programming in VHDL and the consequent difficulty and slowness of implementation can be sidestepped. The text includes a clear theoretical explanation of fuzzy logic (type 1 and type 2) with case studies that implement the theory and systematically demonstrate the implementation process. It goes on to describe basic and advanced levels of programming LabVIEW FPGA and show how implementation of fuzzy-logic control in FPGAs improves system responses. A complete toolkit for implementing fuzzy controllers in LabVIEW FPGA has been developed with the book so that readers can generate new fuzzy controllers and deploy them immediately. Problems and their solutions allow readers to practice the techniques and to absorb the theoretical ideas as they arise. Fuzzy Logic Type 1 and Type 2 Based on LabVIEW FPGA™, helps students studying embedded control systems to design and program those controllers more efficiently and to understand the benefits of using fuzzy logic in doing so. Researchers working with FPGAs find the text useful as an introduction to LabVIEW and as a tool helping them design embedded systems.
9783319266565
10.1007/978-3-319-26656-5 doi
Computational intelligence.
Electronic circuits.
Artificial intelligence.
Computational Intelligence.
Electronic Circuits and Systems.
Artificial Intelligence.
Q342
006.3