Trends in Systems and Signals
| Authors: | Katayama Tohru, Kyoto University, Japan
McKelvey Tomas, Chalmers University of Technology, Sweden
Sano Akira, Keio University, Japan
Cassandras Christos, Boston University, United States
Campi Marco, University of Brescia, Italy |
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| Topic: | 1.1 Modelling, Identification & Signal Processing |
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| Session: | Trends in Systems and Signals |
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| Keywords: | Systems and signals, Modeling, System identification, Adaptive control, Learning, Discrete event systems, Hybrid systems, Stochastic systems |
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Abstract
This report discusses problems and methodologies that lie in the broad scope of systems and signals, with special focus on modeling, identification and signal processing; adaptation and learning; discrete event and hybrid systems; and stochastic systems. A common theme underlying all these areas is that problems in control systems and signals are usually defined and best studied in the framework of stochastic approaches. Although there are common precepts among all these technologies, there are also many unique topics within each area. Therefore, the current key problems in each technology are explained, followed by a discussion of recent major accomplishments with trends, and finally some forecasts of likely developments are provided. The conclusion summarizes some general forecasts for the overall field of systems and signals.
