Presenting a collection of cutting-edge real-time techniques, tools, and applications for various engineering fields, this reference helps readers develop a thorough understanding of the theory and practical aspects of real-time simulation. It introduces cutting-edge industrial and academic simulation tools and examines a variety of distributed and interactive real-time simulation methods. Content is divided into four sections: basic simulation technologies and fundamentals, real-time simulation for system design, parallel and distributed real-time simulation, and tools and applications. This material covers a wide range of diverse application domains, including control, aerospace, automotive, hydraulics, military, and training.
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Katalin Popovici received her engineer degree in computer science from the University of Oradea, Romania, in 2004 and her Ph.D in micro- and nanoelectronics from Grenoble Institute of Technology, France, in 2008. Between 2005 and 2008, she was a member of the SHAPES (Scalable Software Hardware Computing Architecture Platform for Embedded Systems) European research project, where she worked on hardware-software co-design. Currently, she is a senior software engineer at MathWorks in Natick, Massachusetts, where she works on partitioning and mapping capabilities from Simulink(R) models to embedded and real-time systems, with focus on code generation for multicore and heterogeneous architectures.
Pieter J. Mosterman is a senior research scientist at MathWorks in Natick, Massachusetts, where he works on design automation technologies. He also holds an adjunct professor position in the School of Computer Science at McGill University. Prior to this, he was a research associate at the German Aerospace Center (DLR) in Oberpfaffenhofen. He received his Ph.D in electrical and computer engineering from Vanderbilt University in Nashville, Tennessee, and his MSc in electrical engineering from the University of Twente, The Netherlands. His primary research interests include computer automated multiparadigm modeling with principal applications in design automation, training systems, and fault detection, isolation, and reconfiguration.
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