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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Nikolay V. Kirianaki and Sergey Y. Yurish are the authors of Data Acquisition and Signal Processing for Smart Sensors, published by Wiley.
Advanced microsensor technology is making a significant impact in fields as diverse as wireless communications and automotive, biomedical and chemical engineering. Data Acquisition and Signal Processing for Smart Sensors draws on the authors' collective practical experience in the design of sensor instrumentation to provide a systematic treatment of smart sensors and sensor systems. This unique reference presents an alternative to the classical approach to data acquisition and covers signal processing methods for digital and quasi-digital sensors.
Features Include:
* Introduction to the authors' novel Method of the Dependent Count(tm) for frequency (period) conversion and measurement and its applications.
* Consideration of modern sensor interface circuits and buses, along with an introduction to the Universal Transducer Interface (UTI) and Time to Digital Converter (TDC).
* Methods of frequency-to-code conversion for smart sensors, including direct, indirect, combined, interpolation and Fourier transform based techniques as well as advanced and self-adapting conversion methods.
* Comparative analysis of smart sensor systems with time- and space-division channelling functions.
* Detailed glossary of related terms accompanied by a guide to related web resources.
With coverage ranging from the detailed analysis of available conversion methods to software level smart sensor design, Data Acquisition and Signal Processing for Smart Sensors will have broad appeal amongst instrumentation and measurement professionals. Advanced students and researchers in microelectronics, engineers and developers of microsensor systems will appreciate the comprehensive treatment of this emerging area.
Advanced microsensor technology is making a significant impact in fields as diverse as wireless communications and automotive, biomedical and chemical engineering. Data Acquisition and Signal Processing for Smart Sensors draws on the authors' collective practical experience in the design of sensor instrumentation to provide a systematic treatment of smart sensors and sensor systems. This unique reference presents an alternative to the classical approach to data acquisition and covers signal processing methods for digital and quasi-digital sensors.
Features Include: * Introduction to the authors' novel Method of the Dependent Count(tm) for frequency (period) conversion and measurement and its applications.
* Consideration of modern sensor interface circuits and buses, along with an introduction to the Universal Transducer Interface (UTI) and Time to Digital Converter (TDC).
* Methods of frequency-to-code conversion for smart sensors, including direct, indirect, combined, interpolation and Fourier transform based techniques as well as advanced and self-adapting conversion methods.
* Comparative analysis of smart sensor systems with time- and space-division channelling functions.
* Detailed glossary of related terms accompanied by a guide to related web resources. With coverage ranging from the detailed analysis of available conversion methods to software level smart sensor design, Data Acquisition and Signal Processing for Smart Sensors will have broad appeal amongst instrumentation and measurement professionals. Advanced students and researchers in microelectronics, engineers and developers of microsensor systems will appreciate the comprehensive treatment of this emerging area.
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