Springer Series in Synergetics

Synergetics of Measurement, Prediction and Control

Authors: Grabec, Igor, Sachse, Wolfgang

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About this book

The electronic processing of information permits the construction of intelligent systems capable of carrying out a synergy of autonomous measurement, the modeling of natural laws, the control of processes, and the prediction or forecasting of a large variety of natural phenomena. In this monograph, a statistical description of natural phenomena is used to develop an information processing system capable of modeling non-linear relationships between sensory data. The system, based on self-organized, optimal preservation of empirical information, applies these relationships for prediction and adaptive control.
This monograph is written for students, scientists and engineers in academia and industry who are interested in experimental work related to the adaptive modeling of natural laws, the development of sensory-neural networks, intelligent control, synergetics and informatics. No specific knowledge of advanced mathematics is presupposed. Examples taken from physics, engineering, medicine and economics demonstrate the applicability of such intelligent systems.

Table of contents (14 chapters)

Table of contents (14 chapters)

Buy this book

eBook $99.00
price for USA in USD (gross)
  • ISBN 978-3-642-60336-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $129.00
price for USA in USD
  • ISBN 978-3-642-64359-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Synergetics of Measurement, Prediction and Control
Authors
Series Title
Springer Series in Synergetics
Series Volume
68
Copyright
1997
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-60336-5
DOI
10.1007/978-3-642-60336-5
Softcover ISBN
978-3-642-64359-0
Series ISSN
0172-7389
Edition Number
1
Number of Pages
XX, 458
Topics