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- W4328008068 abstract "This chapter introduces the basis and fundamental concepts about system identification. First, dynamical systems and their basic properties are introduced. System identification is the problem of building mathematical models describing the behavior of a dynamical system based on the observations from the system. Traditionally, there are two levels of system identification problems, i.e., estimation of the uncertain parameters governed in the mathematical model and selection of an appropriate model class representing the underlying dynamical system. In addition, one of the special features of this book is that it will introduce the new third level of system identification using self-calibratable model classes. Real-time system identification is desirable for promptly acquiring information from the system for monitoring and control purposes. The Bayes’ theorem and system identification using Bayesian methods are briefly introduced. Finally, an overview of this book is given with outline of each chapter for the convenience of readers. This book introduces some recent developments in Bayesian real-time system identification. It contains two different perspectives on data processing for system identification, namely centralized and distributed." @default.
- W4328008068 created "2023-03-22" @default.
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- W4328008068 date "2023-01-01" @default.
- W4328008068 modified "2023-09-25" @default.
- W4328008068 title "Introduction" @default.
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- W4328008068 doi "https://doi.org/10.1007/978-981-99-0593-5_1" @default.
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