About this book
Recent rapid developments in computing power, such as parallel processing and neural networks, have stimulated new trends in control. However a discrepancy exists between available computing power and exploitable algorithms obtained classically from control theory. The aim of this book is to address the discrepancy from both the com putational power and control theory viewpoints. Areas such as identification, adaptive control, signal processing and neural networks therefore hold a prominent position in the text presented. The form of the book is such that it should be useful for readers at various levels, particularly those at the research and/or application stage. The book has resulted from the IFAC Workshop on the Mutual Impact of Computing Power and Control Theory, which was held at the Institute of Information Theory and Automation (UTIA), Prague, in September 1992. Organisation of the event was provided jointly by the Department of Adaptive Systems, UTIA, Prague and the School of Engineering and Information Sciences, University of Reading, UK. Selected papers from the Workshop have been chosen to give a good balance across the field, whilst at the same time highlighting important areas for future research. In this way the book represents edited Proceedings from the Workshop. One point, quickly apparent, is the international nature of the presentations themselves, which provide not only a technical appraisal of the field but also inject cultural aspects which are vitally important on the path ahead.
Algebra Processing Signal algorithm algorithms automation complexity control information information theory linear algebra networks neural network optimization organization