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  • Format: ePub

Sensors, Circuits, and Systems for Scientific Instruments: A Unified Approach presents a unified treatment of modern measurement systems by integrating relevant knowledge in sensors, circuits, signal processing, and machine learning. It also presents detailed case studies of several real-life measurement systems to illustrate how theoretical analysis and high-level designs are translated into working scientific instruments. The book is meant for upper-level undergraduate and beginning graduate students in electrical and computer engineering, applied physics, and biomedical engineering. It is…mehr

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Produktbeschreibung
Sensors, Circuits, and Systems for Scientific Instruments: A Unified Approach presents a unified treatment of modern measurement systems by integrating relevant knowledge in sensors, circuits, signal processing, and machine learning. It also presents detailed case studies of several real-life measurement systems to illustrate how theoretical analysis and high-level designs are translated into working scientific instruments. The book is meant for upper-level undergraduate and beginning graduate students in electrical and computer engineering, applied physics, and biomedical engineering. It is designed to fill a gap in the market between books focused on specific components of measurement systems (semiconductor devices, analog circuits, digital signal processing, etc.) and books that provide a high-level "survey" or "handbook"-type overview of a wide range of sensors and measurement systems. - Develops a unified treatment of modern scientific instruments by combining knowledge of high-performance sensors, semiconductor devices, circuits, signal processing, and embedded computing - Focuses on fundamental concepts in precision sensing and interface circuitry (accuracy, precision, linearity, noise, etc.) and their impact on system-level performance instead of presenting a "laundry list" of sensor types - Introduces readers to the indispensable role of signal detection theory, pattern recognition, and machine learning for modern scientific instrumentation - Presents multiple case studies and examples to demonstrate how theoretical concepts are translated into real-life measurement systems

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Autorenporträt
Soumyajit Mandal received his M.S. and Ph.D. degrees in electrical engineering from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, in 2004 and 2009, respectively. He was a Research Scientist with Schlumberger-Doll Research, Cambridge (2010 to 2014), an Assistant Professor with the Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA (2014 to 2019), and an Associate Professor with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA (2019 to 2021). He is currently a Senior Engineer in the Instrumentation Division at Brookhaven National Laboratory, Upton, NY, USA. He has over 150 publications in peer-reviewed journals and conferences and has been awarded 24 patents. His research interests include low-power analog and RF circuits, embedded systems, magnetic resonance sensors, and precision instrumentation for various biomedical and sensor interface applications. Dr. Mandal received the President of India Gold Medal in 2002, the MIT Microsystems Technology Laboratories (MTL) Doctoral Dissertation Award in 2009, the T. Keith Glennan Fellowship in 2016, and the IIT Kharagpur Young Alumni Achievers Award in 2018. He is a Senior Member of the IEEE.