Fuzzy Logic and Intelligent Systems / Edition 1

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Overview

One of the attractions of fuzzy logic is its utility in solving many real engineering problems. As many have realised, the major obstacles in building a real intelligent machine involve dealing with random disturbances, processing large amounts of imprecise data, interacting with a dynamically changing environment, and coping with uncertainty. Neural-fuzzy techniques help one to solve many of these problems.
Fuzzy Logic and Intelligent Systems reflects the most recent developments in neural networks and fuzzy logic, and their application in intelligent systems. In addition, the balance between theoretical work and applications makes the book suitable for both researchers and engineers, as well as for graduate students.

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Editorial Reviews

Booknews
An edited volume consisting of 15 chapters contributed by authors from the US, Canada, Japan, Europe, and India. The subjects presented reflect the most recent developments in neural networks, fuzzy logic, and their applications in intelligent systems. Specific topics include improvement of fuzzy control methods; ordering fuzzy real quantities; fuzzy logic controllers for aircraft flight control; and camcorder operation judgment using a neural computing approach. The balance between theoretical work and applications makes the volume suitable for graduate students as well as researchers and engineers. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780792395751
  • Publisher: Springer Netherlands
  • Publication date: 6/1/1995
  • Series: International Series in Intelligent Technologies , #3
  • Edition description: 1995
  • Edition number: 1
  • Pages: 450
  • Product dimensions: 6.14 (w) x 9.21 (h) x 1.00 (d)

Table of Contents

Preface. 1. Improvement of Fuzzy Control Methods; M. Mizumoto. 2. Neural Networks and Fuzzy Basis Functions for Functional Approximation; Liang Jin, M.M. Gupta, P.N. Nikiforuk. 3. Ordering Fuzzy Real Quantities; R. Lowen. 4. Fuzzy Logic Controllers for Aircraft Flight Control; Jia Luo, E. Lan. 5. A Classical Controller: a Special Case of the Fuzzy Logic Controller; T. Brehm, K. Rattan. 6. Real Time Fuzzy Logic Controller for Balancing a Beam-and-Ball System; N. Godfrey, Hua Li, Yuandong Ji, W. Marcy. 7. Design of Fuzzy Controllers Based on Frequency and Transient Characteristics; K. Tanaka. 8. Fuzzy Inference Integrating 3D Measuring System with Adaptive Sensing Strategy; K. Shimojima, T. Fukuda, F. Arai, H. Matsuura. 9. Robot Hand—Eye Coordination Based on Fuzzy Logic; S. Kumaresan, Hua Li, Xing-Min Li. 10. Using FPGA Technique for Design and Implementation of a Fuzzy Inference System; D. Hung. 11. An Empirical Analysis of One Type of Direct Adaptive Fuzzy Control; H. Bersini, V. Gorrini. 12. Automatic Optimal Design of Fuzzy Systems Based on Universal Approximation and Evolutionary Programming; M. Nyberg, Yoh-Han Pao. 13. Intelligent Control Using Dynamic Neural Networks with Robotic Applications; Liang Jin, M.M. Gupta, P.N. Nikiforuk. 14. Camcorder Operation Judgement Using a Neural Computing Approach; K. Kaneda, P. Wang. 15. Model Reduction and Control of Multistage Flash (MSF) Desalinization Plants; S. Ramamurthy, J. Pal, A. Sinha, D.M.K. Al Gobaisi, G.P. Rao. Index.

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