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Data-Driven Modeling, Filtering and Control - (Control, Robotics and Sensors) by Carlo Novara & Simone Formentin (Hardcover)
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About this item
Highlights
- The scientific research in many engineering fields has been shifting from traditional first-principle-based to data-driven or evidence-based theories.
- Author(s): Carlo Novara & Simone Formentin
- 304 Pages
- Technology, Electronics
- Series Name: Control, Robotics and Sensors
Description
About the Book
Using important examples, this book showcases the potential of the latest data-based and data-driven methodologies for filter and control design. It discusses the most important classes of dynamic systems, along with the statistical and set membership analysis and design frameworks.
Book Synopsis
The scientific research in many engineering fields has been shifting from traditional first-principle-based to data-driven or evidence-based theories. The latter methods may enable better system design, based on more accurate and verifiable information.
In the era of big data, IoT and cyber-physical systems, this subject is of growing importance, as data-driven approaches are key enablers to solve problems that could not be addressed by standard approaches. This book presents a number of innovative data-driven methodologies, complemented by significant application examples, to show the potential offered by the most recent advances in the field. Applicable across a range of disciplines, the topics discussed here will be of interest to scientists, engineers and students in automatic control and learning systems, automotive and aerospace engineering, electrical engineering and signal processing.
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