Industrial and Manufacturing Systems, Vol 4. Neural Network Systems Techniques and Applications

  • ID: 1766459
  • Book
  • 395 Pages
  • Elsevier Science and Technology
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Industrial and Manufacturing Systems serves as an in-depth guide to major applications in this focal area of interest to the engineering community. This volume emphasizes the neural network structures used to achieve practical and effective systems, and provides numerous examples. Industrial and Manufacturing Systems is a unique and comprehensive reference to diverse application methodologies and implementations by means of neural network systems. It willbe of use to practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering.
  • Quality control techniques
  • Active noise and vibration control
  • Chemical processing systems
  • Process monitoring and diagnosis
  • Robotic assembly in electronics manufacturing systems
  • Smart structural systems of improved effectiveness
  • Closed loop feedback control in uncertain nonlinear manufacturing systems
  • Adaptive neural controllers in industrial systems
  • Machine tool control systems

Emphasis is placed on neural network structures for achieving practical and effective systems, with numerous examples illustrating the text; Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering, will find this volume a unique and comprehensive reference to diverse application methodologies and implementations by means of neura network systems.

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Shin, Dynamic Nonlinear Systems: Theory and Application to Tool Wear Monitoring in Flexible Manufacturing Systems. Wang and Chang, Identification of Surface Flaws in Manufacturing System Products. Snyder, Active Noise and Vibration Control Using a Neural Network-based Controller. Loh, pH Processes. Du, Engineering Monitoring and Diagnosis. Chan, Robotic Assembly in Electronics Manufacturing Systems. Damle and Rao, Smart Structural Systems. Kim and Lewis, Dynamic Neural Networks for Closed-Loop Feedback Control and Estimation of Uncertain Nonlinear Systems. Sen, Hearn, and Zhang, Adaptive Neural Controller.
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Leondes, Cornelius T.
Cornelius T. Leondes received his B.S., M.S., and Ph.D. from the University of Pennsylvania and has held numerous positions in industrial and academic institutions. He is currently a Professor Emeritus at the University of California, Los Angeles. He has also served as the Boeing Professor at the University of Washington and as an adjunct professor at the University of California, San Diego. He is the author, editor, or co-author of more than 100 textbooks and handbooks and has published more than 200 technical papers. In addition, he has been a Guggenheim Fellow, Fulbright Research Scholar, IEEE Fellow, and a recipient of IEEE's Baker Prize Award and Barry Carlton Award.
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