This book and disk set introduces the fundamentals necessary toapply fuzzy systems, neural networks, and integrated "neurofuzzy"technology to engineering problems using MATLAB. Whether used onits own or as a companion to Fuzzy and Neural Approaches inEngineering by Lefteri H. Tsoukalas and Robert E. Uhrig (Wiley1997), it takes readers step by step from theory to codedevelopment and implementation--enabling students andresearchers to explore the new frontiers in soft computing.
The Supplement features:
* A practical introduction to MATLAB, plus lists of online andother available resources
* MATLAB code demonstrations of theory and architecturesdiscussed in Fuzzy and Neural Approaches in Engineering
* Foundations of fuzzy approaches and relationships, fuzzynumbers, and fuzzy control
* Fundamentals of competitive, associative, and dynamic neuralnetworks and neural control systems
* Practical coverage of neural methods in fuzzy systems and otherhybrid neurofuzzy systems and applications.
System requirements for IBM-compatible disk:
* 486 processor (Pentium recommended)
* 8 MB of RAM (16 MB recommended)
* 5 MB hard disk space
* MATLAB--student or professional edition
* Microsoft Word 6.0 or 7.0.
"Sinopsis" puede pertenecer a otra edición de este libro.
J. WESLEY HINES, PhD, is a research assistant professor in the Nuclear Engineering Department at the University of Tennessee.
This book and disk set introduces the fundamentals necessary to apply fuzzy systems, neural networks, and integrated "neurofuzzy" technology to engineering problems using MATLAB. Whether used on its own or as a companion to Fuzzy and Neural Approaches in Engineering by Lefteri H. Tsoukalas and Robert E. Uhrig (Wiley 1997), it takes readers step by step from theory to code development and implementation—enabling students and researchers to explore the new frontiers in soft computing.
The Supplement features:
System requirements for IBM-compatible disk:
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
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Paperback. Condición: new. Paperback. This book and disk set introduces the fundamentals necessary toapply fuzzy systems, neural networks, and integrated "neurofuzzy"technology to engineering problems using MATLAB. Whether used onits own or as a companion to Fuzzy and Neural Approaches inEngineering by Lefteri H. Tsoukalas and Robert E. Uhrig (Wiley1997), it takes readers step by step from theory to codedevelopment and implementation--enabling students andresearchers to explore the new frontiers in soft computing. The Supplement features: * A practical introduction to MATLAB, plus lists of online andother available resources * MATLAB code demonstrations of theory and architecturesdiscussed in Fuzzy and Neural Approaches in Engineering * Foundations of fuzzy approaches and relationships, fuzzynumbers, and fuzzy control * Fundamentals of competitive, associative, and dynamic neuralnetworks and neural control systems * Practical coverage of neural methods in fuzzy systems and otherhybrid neurofuzzy systems and applications. System requirements for IBM-compatible disk: * 486 processor (Pentium recommended) * 8 MB of RAM (16 MB recommended) * 5 MB hard disk space * MATLAB--student or professional edition * Microsoft Word 6.0 or 7.0. Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. Researchers are applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780471192473
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Condición: New. Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. Researchers are applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. Num Pages: 224 pages, Illustrations. BIC Classification: PBWX; TBC. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 281 x 214 x 11. Weight in Grams: 540. . 1997. 1st Edition. paperback. . . . . Nº de ref. del artículo: V9780471192473
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Condición: New. Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. Researchers are applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. Num Pages: 224 pages, Illustrations. BIC Classification: PBWX; TBC. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 281 x 214 x 11. Weight in Grams: 540. . 1997. 1st Edition. paperback. . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9780471192473
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Paperback. Condición: new. Paperback. This book and disk set introduces the fundamentals necessary toapply fuzzy systems, neural networks, and integrated "neurofuzzy"technology to engineering problems using MATLAB. Whether used onits own or as a companion to Fuzzy and Neural Approaches inEngineering by Lefteri H. Tsoukalas and Robert E. Uhrig (Wiley1997), it takes readers step by step from theory to codedevelopment and implementation--enabling students andresearchers to explore the new frontiers in soft computing. The Supplement features: * A practical introduction to MATLAB, plus lists of online andother available resources * MATLAB code demonstrations of theory and architecturesdiscussed in Fuzzy and Neural Approaches in Engineering * Foundations of fuzzy approaches and relationships, fuzzynumbers, and fuzzy control * Fundamentals of competitive, associative, and dynamic neuralnetworks and neural control systems * Practical coverage of neural methods in fuzzy systems and otherhybrid neurofuzzy systems and applications. System requirements for IBM-compatible disk: * 486 processor (Pentium recommended) * 8 MB of RAM (16 MB recommended) * 5 MB hard disk space * MATLAB--student or professional edition * Microsoft Word 6.0 or 7.0. Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. Researchers are applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9780471192473
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Paperback. Condición: new. Paperback. This book and disk set introduces the fundamentals necessary toapply fuzzy systems, neural networks, and integrated "neurofuzzy"technology to engineering problems using MATLAB. Whether used onits own or as a companion to Fuzzy and Neural Approaches inEngineering by Lefteri H. Tsoukalas and Robert E. Uhrig (Wiley1997), it takes readers step by step from theory to codedevelopment and implementation--enabling students andresearchers to explore the new frontiers in soft computing. The Supplement features: * A practical introduction to MATLAB, plus lists of online andother available resources * MATLAB code demonstrations of theory and architecturesdiscussed in Fuzzy and Neural Approaches in Engineering * Foundations of fuzzy approaches and relationships, fuzzynumbers, and fuzzy control * Fundamentals of competitive, associative, and dynamic neuralnetworks and neural control systems * Practical coverage of neural methods in fuzzy systems and otherhybrid neurofuzzy systems and applications. System requirements for IBM-compatible disk: * 486 processor (Pentium recommended) * 8 MB of RAM (16 MB recommended) * 5 MB hard disk space * MATLAB--student or professional edition * Microsoft Word 6.0 or 7.0. Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. Researchers are applying neural networks and fuzzy systems in series, from the use of fuzzy inputs and outputs for neural networks to the employment of individual neural networks to quantify the shape of a fuzzy membership function. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9780471192473
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Librería: Buchpark, Trebbin, Alemania
Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book and disk set introduces the fundamentals necessary to apply fuzzy systems, neural networks, and integrated "neurofuzzy" technology to engineering problems using MATLAB. Whether used on its own or as a companion to Fuzzy and Neural Approaches in Engineering by Lefteri H. Tsoukalas and Robert E. Uhrig (Wiley 1997), it takes readers step by step from theory to code development and implementation-enabling students and researchers to explore the new frontiers in soft computing. The Supplement features: A practical introduction to MATLAB, plus lists of online and other available resources MATLAB code demonstrations of theory and architectures discussed in Fuzzy and Neural Approaches in Engineering Foundations of fuzzy approaches and relationships, fuzzy numbers, and fuzzy control Fundamentals of competitive, associative, and dynamic neural networks and neural control systems Practical coverage of neural methods in fuzzy systems and other hybrid neurofuzzy systems and applications. System requirements for IBM-compatible disk: 486 processor (Pentium recommended) 8 MB of RAM (16 MB recommended) 5 MB hard disk space MATLAB-student or professional edition Microsoft Word 6.0 or 7.0. Nº de ref. del artículo: 2369026/202
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