Data Acquisition and Signal Processing for Smart Sensors

Download or Read eBook Data Acquisition and Signal Processing for Smart Sensors PDF written by Nikolay V. Kirianaki and published by Wiley. This book was released on 2002-04-29 with total page 298 pages. Available in PDF, EPUB and Kindle.
Data Acquisition and Signal Processing for Smart Sensors
Author :
Publisher : Wiley
Total Pages : 298
Release :
ISBN-10 : 0470843179
ISBN-13 : 9780470843178
Rating : 4/5 (79 Downloads)

Book Synopsis Data Acquisition and Signal Processing for Smart Sensors by : Nikolay V. Kirianaki

Book excerpt: From simple thermistors to intelligent silicon microdevices with powerful capabilities to communicate information across networks, sensors play an important role in such diverse fields as biomedical and chemical engineering to wireless communications. Introducing a new dependent count method for frequency signal processing, this book presents a practical approach to the design of signal processing sensors. Modern advanced microsensors technologies require new and equally advanced methods of frequency signal processing in order to function at inreasingly high speeds. The authors provide a comprehensive overview of data acquisition and signal processing methods for the new generation of smart and quasi-smart sensors. The practical approach of the text includes coverage of the design of signal processing methods for digital, frequency, period, duty-cycle and time interval sensors. * Contains numerous practical examples illustrating the design of unique signal processing sensors and transducers * Details traditional, novel, and state of the art methods for frequency signal processing * Coverage of the physical characteristics of smart sensors, development methods and applications potential * Outlines the concept, principles and nature of the method of dependent count (MDC) ; a unique method for frequency signal processing, developed by the authors This text is a leading edge resource for measurement engineers, researchers and developers working in microsensors, MEMS and microsystems, as well as advanced undergraduates and graduates in electrical and mechanical engineering.


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