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"Integrates a broad range of physics, algorithms, and sensing techniques for development of intelligent systems. Highlights adaptive least-squared error modeling. Covers complex sampling, physical system modeling using digital filters, frequency domain processing, beamforming, and much more."
Book Synopsis Signal Processing for Intelligent Sensor Systems by : David C. Swanson
Download or read book Signal Processing for Intelligent Sensor Systems written by David C. Swanson and published by CRC Press. This book was released on 2000-04-18 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Integrates a broad range of physics, algorithms, and sensing techniques for development of intelligent systems. Highlights adaptive least-squared error modeling. Covers complex sampling, physical system modeling using digital filters, frequency domain processing, beamforming, and much more."
Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.
Book Synopsis Signal Processing for Intelligent Sensor Systems with MATLAB® by : David C. Swanson
Download or read book Signal Processing for Intelligent Sensor Systems with MATLAB® written by David C. Swanson and published by CRC Press. This book was released on 2011-07-21 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.
Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.
Book Synopsis Signal Processing for Intelligent Sensor Systems with MATLAB®, Second Edition by : David C. Swanson
Download or read book Signal Processing for Intelligent Sensor Systems with MATLAB®, Second Edition written by David C. Swanson and published by CRC Press. This book was released on 2011-07-26 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.
Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications—including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.
Book Synopsis Intelligent Sensor Networks by : Fei Hu
Download or read book Intelligent Sensor Networks written by Fei Hu and published by CRC Press. This book was released on 2012-12-15 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications—including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.
This revised edition, issued in paperback, has been expanded to include exercises to reinforce the student's understanding of the concepts introduced. Whilst research continues to advance, the authors' fundamental approach, and their systematic treatment of the issues required to understand this fast-developing, multi-disciplinary field, will ensure that this book is required reading not only for sensor engineers designing intelligent sensor systems but also serves as a course text for graduate students specialising in instrumentation, and those in the final year of relevant undergraduate physics, electronics and other engineering first degrees.
Book Synopsis Intelligent Sensor Systems, by : John Brignell
Download or read book Intelligent Sensor Systems, written by John Brignell and published by CRC Press. This book was released on 1996 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This revised edition, issued in paperback, has been expanded to include exercises to reinforce the student's understanding of the concepts introduced. Whilst research continues to advance, the authors' fundamental approach, and their systematic treatment of the issues required to understand this fast-developing, multi-disciplinary field, will ensure that this book is required reading not only for sensor engineers designing intelligent sensor systems but also serves as a course text for graduate students specialising in instrumentation, and those in the final year of relevant undergraduate physics, electronics and other engineering first degrees.
With contributions from an internationally-renowned group of experts, this book uses a multidisciplinary approach to review recent developments in the field of smart sensor systems, covering important system and design aspects. It examines topics over the whole range of sensor technology from the theory and constraints of basic elements, physics and electronics, up to the level of application-orientated issues. Developed as a complementary volume to ‘Smart Sensor Systems’ (Wiley 2008), which introduces the basics of smart sensor systems, this volume focuses on emerging sensing technologies and applications, including: State-of-the-art techniques for designing smart sensors and smart sensor systems, including measurement techniques at system level, such as dynamic error correction, calibration, self-calibration and trimming. Circuit design for sensor systems, such as the design of precision instrumentation amplifiers. Impedance sensors, and the associated measurement techniques and electronics, that measure electrical characteristics to derive physical and biomedical parameters, such as blood viscosity or growth of micro-organisms. Complete sensor systems-on-a-chip, such as CMOS optical imagers and microarrays for DNA detection, and the associated circuit and micro-fabrication techniques. Vibratory gyroscopes and the associated electronics, employing mechanical and electrical signal amplification to enable low-power angular-rate sensing. Implantable smart sensors for neural interfacing in bio-medical applications. Smart combinations of energy harvesters and energy-storage devices for autonomous wireless sensors. Smart Sensor Systems: Emerging Technologies and Applications will greatly benefit final-year undergraduate and postgraduate students in the areas of electrical, mechanical and chemical engineering, and physics. Professional engineers and researchers in the microelectronics industry, including microsystem developers, will also find this a thorough and useful volume.
Book Synopsis Smart Sensor Systems by : Gerard Meijer
Download or read book Smart Sensor Systems written by Gerard Meijer and published by John Wiley & Sons. This book was released on 2014-04-02 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: With contributions from an internationally-renowned group of experts, this book uses a multidisciplinary approach to review recent developments in the field of smart sensor systems, covering important system and design aspects. It examines topics over the whole range of sensor technology from the theory and constraints of basic elements, physics and electronics, up to the level of application-orientated issues. Developed as a complementary volume to ‘Smart Sensor Systems’ (Wiley 2008), which introduces the basics of smart sensor systems, this volume focuses on emerging sensing technologies and applications, including: State-of-the-art techniques for designing smart sensors and smart sensor systems, including measurement techniques at system level, such as dynamic error correction, calibration, self-calibration and trimming. Circuit design for sensor systems, such as the design of precision instrumentation amplifiers. Impedance sensors, and the associated measurement techniques and electronics, that measure electrical characteristics to derive physical and biomedical parameters, such as blood viscosity or growth of micro-organisms. Complete sensor systems-on-a-chip, such as CMOS optical imagers and microarrays for DNA detection, and the associated circuit and micro-fabrication techniques. Vibratory gyroscopes and the associated electronics, employing mechanical and electrical signal amplification to enable low-power angular-rate sensing. Implantable smart sensors for neural interfacing in bio-medical applications. Smart combinations of energy harvesters and energy-storage devices for autonomous wireless sensors. Smart Sensor Systems: Emerging Technologies and Applications will greatly benefit final-year undergraduate and postgraduate students in the areas of electrical, mechanical and chemical engineering, and physics. Professional engineers and researchers in the microelectronics industry, including microsystem developers, will also find this a thorough and useful volume.
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.
Book Synopsis Data Acquisition and Signal Processing for Smart Sensors by : Nikolay V. Kirianaki
Download or read book Data Acquisition and Signal Processing for Smart Sensors 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. 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.
Intelligent seonsors are revolutionizing the world of system design in everything from sports cars to assembly lines. These new sensors have abilities that leave their predecessors in the dust! They not only measure parameters efficiently and precisely, but they also have the ability to enhance and interupt those measurements, thereby transforming raw data into truly useful information. Unlike many embedded systems books that confine themselves strictly to firmware and software, this book also delves into the supporting electronic hardware, providing the reader with a complete understanding of the issues involved when interfacing to specific types of sensor and offering insight into the real-world problems designers will face. The examples provide a complete, easily extensible code framework for sensor-based applications as well as basic support routines that are often ignored or treated superficially. The goal throughout is to make readers truly productive as quickly as possible while providing the thorough understanding necessary to design robust systems. Readers will gain in-depth, real-world design information that will help them be more productive and get up to speed on sensor design skills more quickly. The book provides designers and students a leg up in a relatively new design area, imparting knowledge about a new microcontroller that offers some of the functionality of a DSP chip. Quickly teaches the reader to design the new wave in sensor technology, "intelligent" sensors In-depth design techniques, real-world examples, detailed figures and usable code Application chapters thoroughly exploring temperature, pressure and load, and flow sensors
Book Synopsis Intelligent Sensor Design Using the Microchip dsPIC by : Creed Huddleston
Download or read book Intelligent Sensor Design Using the Microchip dsPIC written by Creed Huddleston and published by Elsevier. This book was released on 2006-12-18 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent seonsors are revolutionizing the world of system design in everything from sports cars to assembly lines. These new sensors have abilities that leave their predecessors in the dust! They not only measure parameters efficiently and precisely, but they also have the ability to enhance and interupt those measurements, thereby transforming raw data into truly useful information. Unlike many embedded systems books that confine themselves strictly to firmware and software, this book also delves into the supporting electronic hardware, providing the reader with a complete understanding of the issues involved when interfacing to specific types of sensor and offering insight into the real-world problems designers will face. The examples provide a complete, easily extensible code framework for sensor-based applications as well as basic support routines that are often ignored or treated superficially. The goal throughout is to make readers truly productive as quickly as possible while providing the thorough understanding necessary to design robust systems. Readers will gain in-depth, real-world design information that will help them be more productive and get up to speed on sensor design skills more quickly. The book provides designers and students a leg up in a relatively new design area, imparting knowledge about a new microcontroller that offers some of the functionality of a DSP chip. Quickly teaches the reader to design the new wave in sensor technology, "intelligent" sensors In-depth design techniques, real-world examples, detailed figures and usable code Application chapters thoroughly exploring temperature, pressure and load, and flow sensors
"IEEE Press is proud to present the first selected reprint volume devoted to the new field of intelligent signal processing (ISP). ISP differs fundamentally from the classical approach to statistical signal processing in that the input-output behavior of a complex system is modeled by using "intelligent" or "model-free" techniques, rather than relying on the shortcomings of a mathematical model. Information is extracted from incoming signal and noise data, making few assumptions about the statistical structure of signals and their environment. Intelligent Signal Processing explores how ISP tools address the problems of practical neural systems, new signal data, and blind fuzzy approximators. The editors have compiled 20 articles written by prominent researchers covering 15 diverse, practical applications of this nascent topic, exposing the reader to the signal processing power of learning and adaptive systems. This essential reference is intended for researchers, professional engineers, and scientists working in statistical signal processing and its applications in various fields such as humanistic intelligence, stochastic resonance, financial markets, optimization, pattern recognition, signal detection, speech processing, and sensor fusion. Intelligent Signal Processing is also invaluable for graduate students and academics with a background in computer science, computer engineering, or electrical engineering. About the Editors Simon Haykin is the founding director of the Communications Research Laboratory at McMaster University, Hamilton, Ontario, Canada, where he serves as university professor. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" (Publisher) and is both an IEEE Fellow and Fellow of the Royal Society of Canada. Bart Kosko is a past director of the University of Southern California's (USC) Signal and Image Processing Institute. He has authored several books, including Neural Networks and Fuzzy Systems, Neural Networks for Signal Processing (Publisher, copyright date) and Fuzzy Thinking (Publisher, copyright date), as well as the novel Nanotime (Publisher, copyright date). Dr. Kosko is an elected governor of the International Neural Network Society and has chaired many neural and fuzzy system conferences. Currently, he is associate professor of electrical engineering at USC."
Book Synopsis Intelligent Signal Processing by : Simon Haykin
Download or read book Intelligent Signal Processing written by Simon Haykin and published by Wiley-IEEE Press. This book was released on 2001-01-15 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: "IEEE Press is proud to present the first selected reprint volume devoted to the new field of intelligent signal processing (ISP). ISP differs fundamentally from the classical approach to statistical signal processing in that the input-output behavior of a complex system is modeled by using "intelligent" or "model-free" techniques, rather than relying on the shortcomings of a mathematical model. Information is extracted from incoming signal and noise data, making few assumptions about the statistical structure of signals and their environment. Intelligent Signal Processing explores how ISP tools address the problems of practical neural systems, new signal data, and blind fuzzy approximators. The editors have compiled 20 articles written by prominent researchers covering 15 diverse, practical applications of this nascent topic, exposing the reader to the signal processing power of learning and adaptive systems. This essential reference is intended for researchers, professional engineers, and scientists working in statistical signal processing and its applications in various fields such as humanistic intelligence, stochastic resonance, financial markets, optimization, pattern recognition, signal detection, speech processing, and sensor fusion. Intelligent Signal Processing is also invaluable for graduate students and academics with a background in computer science, computer engineering, or electrical engineering. About the Editors Simon Haykin is the founding director of the Communications Research Laboratory at McMaster University, Hamilton, Ontario, Canada, where he serves as university professor. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" (Publisher) and is both an IEEE Fellow and Fellow of the Royal Society of Canada. Bart Kosko is a past director of the University of Southern California's (USC) Signal and Image Processing Institute. He has authored several books, including Neural Networks and Fuzzy Systems, Neural Networks for Signal Processing (Publisher, copyright date) and Fuzzy Thinking (Publisher, copyright date), as well as the novel Nanotime (Publisher, copyright date). Dr. Kosko is an elected governor of the International Neural Network Society and has chaired many neural and fuzzy system conferences. Currently, he is associate professor of electrical engineering at USC."
In recent years, MEMS have revolutionized the semiconductor industry, with sensors being a particularly buoyant sector. Smart MEMS and Sensor Systems presents readers with the means to understand, evaluate, appreciate and participate in the development of the field, from a unique systems perspective. The combination of MEMS and integrated intelligence has been put forward as a disruptive technology. The full potential of this technology is only evident when it is used to construct very large pervasive sensing systems. The book explores the many different technologies needed to build such systems and integrates knowledge from three different domains: MEMS technology, sensor system electronics and pervasive computing science. Throughout the book a top-down design perspective is taken, be it for the development of a single smart sensor or that of adaptive ad-hoc networks of millions of sensors. For experts in any of the domains named above the book provides the context for their MEMS based design work and an understanding of the role the other domains play. For the generalist (either in engineering or computing) or the technology manager the underpinning knowledge is provided, which can inform specialist decision making. Contents: Markets and ApplicationsMicrofabrication TechnologiesSensor ElectronicsSensor Signal EnhancementCase Study: Control Systems for Capacitive Inertial SensorsCase Study: Adaptive Optics and Smart VLSI/MEMS SystemsArtificial Intelligence Techniques for Microsensors Identification and CompensationSmart, Intelligent and Cogent MEMS Based SensorsSensor Arrays and NetworksWireless and Ad Hoc Sensor NetworksRealising the Dream — A Case Study Readership: Graduate students on courses in sensing, instrumentation, VLSI, and MEMS technology; researchers and academics dealing with smart sensor systems; practitioners who need to understand and apply the technology effectively. Key Features:Provides a unique systems perspective on established MEMS sensor design techniquesPresents state-of-the-art developments through surveys and original research by the authorsIntroduces new ideas for future designs of intelligent and cogent/autonomous sensors and sensor networksHas a good balance of technology/fabrication processes vs signal processing and concept- level discussionAims at the multidisciplinary community involved in designing, producing and using MEMS sensorsKeywords:MEMS;Sensor;Smart;Intelligent;Distributed Systems
Book Synopsis Smart MEMS and Sensor Systems by : Elena Gaura
Download or read book Smart MEMS and Sensor Systems written by Elena Gaura and published by World Scientific. This book was released on 2006-08-10 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, MEMS have revolutionized the semiconductor industry, with sensors being a particularly buoyant sector. Smart MEMS and Sensor Systems presents readers with the means to understand, evaluate, appreciate and participate in the development of the field, from a unique systems perspective. The combination of MEMS and integrated intelligence has been put forward as a disruptive technology. The full potential of this technology is only evident when it is used to construct very large pervasive sensing systems. The book explores the many different technologies needed to build such systems and integrates knowledge from three different domains: MEMS technology, sensor system electronics and pervasive computing science. Throughout the book a top-down design perspective is taken, be it for the development of a single smart sensor or that of adaptive ad-hoc networks of millions of sensors. For experts in any of the domains named above the book provides the context for their MEMS based design work and an understanding of the role the other domains play. For the generalist (either in engineering or computing) or the technology manager the underpinning knowledge is provided, which can inform specialist decision making. Contents: Markets and ApplicationsMicrofabrication TechnologiesSensor ElectronicsSensor Signal EnhancementCase Study: Control Systems for Capacitive Inertial SensorsCase Study: Adaptive Optics and Smart VLSI/MEMS SystemsArtificial Intelligence Techniques for Microsensors Identification and CompensationSmart, Intelligent and Cogent MEMS Based SensorsSensor Arrays and NetworksWireless and Ad Hoc Sensor NetworksRealising the Dream — A Case Study Readership: Graduate students on courses in sensing, instrumentation, VLSI, and MEMS technology; researchers and academics dealing with smart sensor systems; practitioners who need to understand and apply the technology effectively. Key Features:Provides a unique systems perspective on established MEMS sensor design techniquesPresents state-of-the-art developments through surveys and original research by the authorsIntroduces new ideas for future designs of intelligent and cogent/autonomous sensors and sensor networksHas a good balance of technology/fabrication processes vs signal processing and concept- level discussionAims at the multidisciplinary community involved in designing, producing and using MEMS sensorsKeywords:MEMS;Sensor;Smart;Intelligent;Distributed Systems
