C++ Neural Networks and Fuzzy Logic
Author | : Hayagriva V. Rao |
Publisher | : |
Total Pages | : 551 |
Release | : 1996 |
Genre | : C++ (Computer program language) |
ISBN | : 9788170296942 |
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Author | : Hayagriva V. Rao |
Publisher | : |
Total Pages | : 551 |
Release | : 1996 |
Genre | : C++ (Computer program language) |
ISBN | : 9788170296942 |
Author | : Granino Arthur Korn |
Publisher | : MIT Press (MA) |
Total Pages | : 418 |
Release | : 1995 |
Genre | : Computers |
ISBN | : |
Neural Networks and Fuzzy-Logic Control introduces a simple integrated environment for programming displays and report generation. It includes the only currently available software that permits combined simulation of multiple neural networks, fuzzy-logic controllers, and dynamic systems such as robots or physiological models. The enclosed educational version of DESIRE/NEUNET differs for the full system mainly in the size of its data area and includes a compiler, two screen editors, color graphics, and many ready-to-run examples. The software lets users or instructors add their own help screens and interactive menus. The version of DESIRE/NEUNET included here is for PCs, viz. 286/287, 386/387, 486DX, Pentium, P6, SX with math coprocessor.
Author | : Lakhmi C. Jain |
Publisher | : CRC Press |
Total Pages | : 363 |
Release | : 2020-01-29 |
Genre | : Computers |
ISBN | : 1000715124 |
Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.
Author | : Vojislav Kecman |
Publisher | : MIT Press |
Total Pages | : 556 |
Release | : 2001 |
Genre | : Computers |
ISBN | : 9780262112550 |
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.
Author | : Chi-hau Chen |
Publisher | : McGraw-Hill Companies |
Total Pages | : 862 |
Release | : 1996 |
Genre | : Computers |
ISBN | : |
A practical reference that presents concise and comprehensive reports on the major activities in fuzzy logic and neural networks, with emphasis on the applications and systems of interest to computer engineers. Each of the 31 chapters focuses on the most important activity of a specific topic, and the chapters are organized into three parts: principles and algorithms; applications; and architectures and systems. The applications for fuzzy logic include home appliance design and manufacturing process; those for neural networks include radar, sonar, and speech signal processing, remote sensing, and electrical power systems. Annotation copyright by Book News, Inc., Portland, OR
Author | : Stephen T. Welstead |
Publisher | : |
Total Pages | : |
Release | : 2005 |
Genre | : |
ISBN | : |
Author | : Nikola K. Kasabov |
Publisher | : Marcel Alencar |
Total Pages | : 581 |
Release | : 1996 |
Genre | : Artificial intelligence |
ISBN | : 0262112124 |
Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.
Author | : Stephen T. Welstead |
Publisher | : Wiley |
Total Pages | : 494 |
Release | : 1994-07-13 |
Genre | : Computers |
ISBN | : 9780471309741 |
Using an engineering and science perspective, it explores diverse neural network, fuzzy logic and genetic algorithm techniques plus developing applications best suited for each of the methods discussed. Sample results are described and judgment made as to how well each application worked. The book/disk set includes an object-oriented user interface along with the code for numerous programs.
Author | : Stephen T Welstead |
Publisher | : |
Total Pages | : |
Release | : 1994-08-01 |
Genre | : |
ISBN | : 9785554800092 |
Author | : Masao Mukaidono |
Publisher | : World Scientific |
Total Pages | : 117 |
Release | : 2001 |
Genre | : Computers |
ISBN | : 9810245343 |
There are many uncertainties in the real world. Fuzzy theory treats a kind of uncertainty called fuzziness, where it shows that the boundary of yes or no is ambiguous and appears in the meaning of words or is included in the subjunctives or recognition of human beings. Fuzzy theory is essential and is applicable to many systems -- from consumer products like washing machines or refrigerators to big systems like trains or subways. Recently, fuzzy theory has been a strong tool for combining new theories (called soft computing) such as genetic algorithms or neural networks to get knowledge from real data. This introductory book enables the reader to understand easily what fuzziness is and how one can apply fuzzy theory to real problems -- which explains why it was a best-seller in Japan.