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A handbook on recent advancements and the state of the art in array processing and sensor Networks
Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks.
Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in…mehr
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A handbook on recent advancements and the state of the art in array processing and sensor Networks
Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks.
Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks.
Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.
Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks.
Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks.
Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.
Produktdetails
- Produktdetails
- Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control Vol.1
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 924
- Erscheinungstermin: 1. Januar 2010
- Englisch
- Abmessung: 260mm x 183mm x 54mm
- Gewicht: 1667g
- ISBN-13: 9780470371763
- ISBN-10: 0470371765
- Artikelnr.: 25933929
- Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control Vol.1
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 924
- Erscheinungstermin: 1. Januar 2010
- Englisch
- Abmessung: 260mm x 183mm x 54mm
- Gewicht: 1667g
- ISBN-13: 9780470371763
- ISBN-10: 0470371765
- Artikelnr.: 25933929
Simon Haykin, PhD, is a Distinguished University Professor at McMaster University, Hamilton, Ontario. K. J. Ray Liu is a Distinguished Scholar-Teacher at the University of Maryland, College Park. He is the recipient of numerous honors and awards including best paper awards from IEEE Signal Processing Society, IEEE Vehicular Technology Society, and EURASIP, as well as recognition from the University of Maryland, including Invention of the Year Award, Poole and Kent Senior Faculty Teaching Award, and Outstanding Faculty Research Award. Dr. Liu is a Fellow of the IEEE and AAAS.
Preface (Simon Haykin and K. J. Ray Liu). Contributors. Introduction (Simon
Haykin). PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING. 1.
Wavefields. (Alfred Hanssen). 1.1 Introduction. 1.2 Harmonizable Stochastic
Processes. 1.3 Stochastic Wavefields. 1.4 Wave Dispersion. 1.5 Conclusions.
1.6 Acknowledgements. References. 2. Spatial Spectrum Estimation (Petar M.
Djuri). 2.1 Introduction. 2.2 Fundamentals. 2.3 Temporal Spectrum
Estimation. 2.4 Spatial Spectrum Estimation. 2.5 Final Remarks. References.
3. MIMO Radio Propagation (Tricia J. Willink). 3.1 Introduction. 3.2
Space-Time Propagation Environment. 3.3 Propagation Models. 3.4 Measured
Channel Characteristics. 3.5 Stationarity. 3.6 Summary. References. 4.
Robustness Issues in Sensor Array Processing (Alex B. Gershman). 4.1
Introduction. 4.2 Direction-of-Arrival Estimation. 4.3 Adaptive
Beamforming. 4.4 Conclusions. Acknowledgments. References. 5. Wireless
Communication and Sensing in Multipath Environments Using Multiantenna
Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan). 5.1 Introduction
and Overview. 5.2 Multipath Wireless Channel Modeling in Time, Frequency
and Space. 5.3 Point-to-Point MIMO Wireless Communication Systems. 5.4
Active Wireless Sensing with Wideband MIMO Transceivers. 5.5 Concluding
Remarks. References. PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF
ARRAY SIGNAL PROCESSING. 6. Implicit Training and Array Processing for
Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and
Desmond C. McLernon). 6.1 Introduction. 6.2 Classification of Implicit
Training Methods. 6.3 IT-Based Estimation for a Single User. 6.4 IT-Based
Estimation for Multiple Users Exploiting Array Processing: Continuous
Transmission. 6.5 IT-Based Estimation for Multiple Users Exploiting Array
Processing: Packet Transmission. 6.6 Open Research Problems.
Acknowledgments. References. 7. Unitary Design of Radar Waveform Diversity
Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill
Moran). 7.1 Introduction. 7.2 2 x 2 Space-Time Diversity Waveform Design.
7.3 4 x 4 Space-Time Diversity Waveform Design. 7.4 Waveform Families Based
on Kronecker Products. 7.5 Introduction to Data-Dependent Waveform Design.
7.6 3 x 3 and 6 x 6 Waveform Scheduling. 7.7 Summary. References. 8.
Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard
Hänsler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff). 8.1
Introduction. 8.2 Signal Processing in the Subband Domain. 8.3 Multichannel
Echo Cancelation. 8.4 Speaker Localization. 8.5 Beamforming. 8.6 Sensor
Calibration. 8.7 Postprocessing. 8.8 Conclusions. References. 9. Acoustic
Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc
Moonen and Ann Spriet). 9.1. Introduction. 9.2. Overview of noise reduction
techniques. 9.3. Monaural beamforming. 9.4. Binaural beamforming. 9.5.
Conclusion. 10. Undetermined Blind Source Separation Using Acoustic Arrays
(Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada). 10.1
Introduction. 10.2 Underdetermined Blind Source Separation of Speeches in
Reverberant Environments. 10.3 Sparseness of Speech Sources. 10.4 Binary
Mask Approach to Underdetermined BSS. 10.5 MAP-Based Two-Stage Approach to
Underdetermined BSS. 10.6 Experimental Comparison with Binary Mask Approach
and MAP-Based Two-Stage Approach. 10.7 Concluding Remarks. References. 11.
Array Processing in Astronomy (Douglas C.-J. Bock). 11.1 Introduction. 11.2
Correlation Arrays. 11.3 Aperture Plane Phased Arrays. 11.4 Future
Directions. 11.5 Conclusion. References. 12. Digital 3D/4D Ultrasound
Imaging Array (Stergios Stergiopoulos). 12.1 Background. 12.2 Next
Generation 3D/4D Ultrasound Imaging Technology. 12.3 Computing Architecture
and Implementation Issues. 12.4 An Experimental Planar Array Ultrasound
Imaging System. 12.5 Conclusion. References. PART III: FUNDAMENTAL ISSUES
IN DISTRIBUTED SENSOR NETWORKS. 13. Self-Localization of Sensor Networks
(Josh N. Ash and Randolph L. Moses). 13.1 Introduction. 13.2 Measurement
Types and Performance Bounds. 13.3 Localization Algorithms. 13.4 Relative
and Transformation Error Decomposition. 13.5 Conclusions. References. 14.
Multitarget Tracking and Classification in Collaborative Sensor Networks
via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang). 14.1
Introduction. 14.2 System Description and Problem Formulation. 14.3
Sequential Monte Carlo Methods. 14.4 Joint Single-Target Tracking and
Classification. 14.5 Multiple-Target Tracking and Classification. 14.6
Sensor Selection. 14.7 Simulation Results. Conclusion. Appendix:
Derviations of (14.38 and (14.40). References. 15. Energy-Efficient
Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo).
15.5 Introduction. 15.2 System Model. 15.3 Digital Approaches. 15.4 Analog
Approaches. 15.5 Analog versus Digital. 15.6 Extension to Vector Model.
15.7 Concluding Remarks. Acknowledgments. References. 16. Sensor Data
Fusion with Application to Multitarget Tracking (R. Tharmarasa, K.
Punithakumar, T. Kirubarajan and Y. Bar-Shalom). 16.1 Introduction. 16.2
Tracking Filters. 16.3 Data Association. 16.4 Out-of-Sequence Measurements.
16.5 Results with Real Data. 16.6 Summary. References. 17. Distributed
Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and José Moura).
17.1 Introduction. 17.2 Preliminaries. 17.3 Distributed Detection. 17.4
Consensus Algorithms. 17.5 Zero-Dimension (Average) Consensus. 17.6
Consensus in Higher Dimensions. 17.7 Leader-Follower (Type) Algorithms.
17.8 Localization in Sensor Networks. 17.9 Linear System of Equations:
Distributed Algorithm. 17.10 Conclusions. References. 18. Cooperative
Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu). 18.1
Introduction. 18.2 Cooperative Relay Protocols. 18.3 SER Analysis and
Optimal Power Allocation. 18.4 Energy Efficiency in Cooperative Sensor
Networks. 18.5 Experimental Results. 18.6 Conclusions. References. 19.
Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang
Yang). 19.1 Introduction. 19.2 Theoretical Background. 19.3 Code Designs.
19.4 Applications. 19.5 Conclusions. References. 20. Network Coding for
Sensor Networks (Christina Fragouli). 20.1 Introduction. 20.2 How Can We
Implement Network Coding in a Practical Sensor Network? 20.3 Data
Collection and Coupon Collector Problem. 20.4 Distributed Storage and
Sensor Network Data Persistence. 20.5 Decentralized Operation and Untuned
Radios. 20.6 Broadcasting and Multipath Diversity. 20.7 Network, Channel
and Source Coding. 20.8 Identity-Aware Sensor Networks. 20.9 Discussion.
Acknowledgments. References. 21. Information-Theoretic Studies of Wireless
Sensor Networks (Liang-Liang Xie and P. R. Kumar). 21.1 Introduction. 21.2
Information-Theoretic Studies. 21.3 Relay Schemes. 21.4 Wireless Network
Coding. 21.5 Concluding Remarks. Acknowledgments. References. PART IV:
NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS. 22.
Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S.
Cattivelli). 22.1 Introduction. 22.2 Motivation. 22.3 Incremental Adaptive
Solutions. 22.4 Diffusion Adaptive Solutions. 22.5 Concluding Remarks.
Acknowledgments. References 23. Routing for Statistical Inference in Sensor
Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong). 23.1
Introduction. 23.2 Spatial Data Correlation. 23.3 Statistical Inference of
Markov Random Fields. 23.4 Optimal Routing for Inference with Local
Processing. 23.5 Conclusion and Future Work. 23.6 Bibliographic Notes.
References. 24. Spectral Estimation in Cognitive Radios (Behrouz
Farhang-Boroujeny). 24.1 Filter Bank Formulation of Spectral Estimators.
24.2 Polyphase Realization of Uniform Filter Banks. 24.3 Periodogram
Spectral Estimator. 24.4 Multitaper Spectral Estimator. 24.5 Filter Bank
Spectral Estimator. 24.6 Distributed Spectrum Sensing. 24.7 Discussion.
Appendix A: Effective Degree of Freedom. Appendix B: Explanation to the
Results of Table 24.1. References. 25. Nonparametric Techniques for
Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and
Kostas N. Plataniotis). 25.1 Introduction. 25.2 WLAN Positioning
Architectures. 25.3 Signal Models. 25.4 Zero-Memory Positioning. 25.5
Dynamic Positioning Systems. 25.6 Cognition and Feedback. 25.7 Tracking
Example. 25.8 Conclusions. References. 26. Reconfigurable Self-Activating
Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell). 26.1
Introduction. 26.2 Biosensors Built of Ion Channels. 26.3 Joint Input
Excitation and Concentration Classification for Biosensor. 26.4
Decentralized Deployment of Dense Network of Biosensors. 26.5 Discussion
and Extensions. References. 27. Biochemical Transport Modeling, Estimation
and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ).
27.1 Introduction. 27.2 Physical and Statistical Models. 27.3 Transport
Modeling Using Monte Carlo Approximation. 27.4 Localizing the Source(s).
27.5 Sequential Detection. 27.6 Conclusion. References. 28. Security and
Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig).
28.1 Introduction. 28.2 Security and Privacy Challenges. 28.3 Ensuring
Integrity of Measurement Process. 28.4 Availability Attacks against the
Wireless Link. 28.5 Ensuring Privacy of Routing Contexts. 28.6 Conclusion.
References. Index.
Haykin). PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING. 1.
Wavefields. (Alfred Hanssen). 1.1 Introduction. 1.2 Harmonizable Stochastic
Processes. 1.3 Stochastic Wavefields. 1.4 Wave Dispersion. 1.5 Conclusions.
1.6 Acknowledgements. References. 2. Spatial Spectrum Estimation (Petar M.
Djuri). 2.1 Introduction. 2.2 Fundamentals. 2.3 Temporal Spectrum
Estimation. 2.4 Spatial Spectrum Estimation. 2.5 Final Remarks. References.
3. MIMO Radio Propagation (Tricia J. Willink). 3.1 Introduction. 3.2
Space-Time Propagation Environment. 3.3 Propagation Models. 3.4 Measured
Channel Characteristics. 3.5 Stationarity. 3.6 Summary. References. 4.
Robustness Issues in Sensor Array Processing (Alex B. Gershman). 4.1
Introduction. 4.2 Direction-of-Arrival Estimation. 4.3 Adaptive
Beamforming. 4.4 Conclusions. Acknowledgments. References. 5. Wireless
Communication and Sensing in Multipath Environments Using Multiantenna
Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan). 5.1 Introduction
and Overview. 5.2 Multipath Wireless Channel Modeling in Time, Frequency
and Space. 5.3 Point-to-Point MIMO Wireless Communication Systems. 5.4
Active Wireless Sensing with Wideband MIMO Transceivers. 5.5 Concluding
Remarks. References. PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF
ARRAY SIGNAL PROCESSING. 6. Implicit Training and Array Processing for
Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and
Desmond C. McLernon). 6.1 Introduction. 6.2 Classification of Implicit
Training Methods. 6.3 IT-Based Estimation for a Single User. 6.4 IT-Based
Estimation for Multiple Users Exploiting Array Processing: Continuous
Transmission. 6.5 IT-Based Estimation for Multiple Users Exploiting Array
Processing: Packet Transmission. 6.6 Open Research Problems.
Acknowledgments. References. 7. Unitary Design of Radar Waveform Diversity
Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill
Moran). 7.1 Introduction. 7.2 2 x 2 Space-Time Diversity Waveform Design.
7.3 4 x 4 Space-Time Diversity Waveform Design. 7.4 Waveform Families Based
on Kronecker Products. 7.5 Introduction to Data-Dependent Waveform Design.
7.6 3 x 3 and 6 x 6 Waveform Scheduling. 7.7 Summary. References. 8.
Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard
Hänsler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff). 8.1
Introduction. 8.2 Signal Processing in the Subband Domain. 8.3 Multichannel
Echo Cancelation. 8.4 Speaker Localization. 8.5 Beamforming. 8.6 Sensor
Calibration. 8.7 Postprocessing. 8.8 Conclusions. References. 9. Acoustic
Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc
Moonen and Ann Spriet). 9.1. Introduction. 9.2. Overview of noise reduction
techniques. 9.3. Monaural beamforming. 9.4. Binaural beamforming. 9.5.
Conclusion. 10. Undetermined Blind Source Separation Using Acoustic Arrays
(Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada). 10.1
Introduction. 10.2 Underdetermined Blind Source Separation of Speeches in
Reverberant Environments. 10.3 Sparseness of Speech Sources. 10.4 Binary
Mask Approach to Underdetermined BSS. 10.5 MAP-Based Two-Stage Approach to
Underdetermined BSS. 10.6 Experimental Comparison with Binary Mask Approach
and MAP-Based Two-Stage Approach. 10.7 Concluding Remarks. References. 11.
Array Processing in Astronomy (Douglas C.-J. Bock). 11.1 Introduction. 11.2
Correlation Arrays. 11.3 Aperture Plane Phased Arrays. 11.4 Future
Directions. 11.5 Conclusion. References. 12. Digital 3D/4D Ultrasound
Imaging Array (Stergios Stergiopoulos). 12.1 Background. 12.2 Next
Generation 3D/4D Ultrasound Imaging Technology. 12.3 Computing Architecture
and Implementation Issues. 12.4 An Experimental Planar Array Ultrasound
Imaging System. 12.5 Conclusion. References. PART III: FUNDAMENTAL ISSUES
IN DISTRIBUTED SENSOR NETWORKS. 13. Self-Localization of Sensor Networks
(Josh N. Ash and Randolph L. Moses). 13.1 Introduction. 13.2 Measurement
Types and Performance Bounds. 13.3 Localization Algorithms. 13.4 Relative
and Transformation Error Decomposition. 13.5 Conclusions. References. 14.
Multitarget Tracking and Classification in Collaborative Sensor Networks
via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang). 14.1
Introduction. 14.2 System Description and Problem Formulation. 14.3
Sequential Monte Carlo Methods. 14.4 Joint Single-Target Tracking and
Classification. 14.5 Multiple-Target Tracking and Classification. 14.6
Sensor Selection. 14.7 Simulation Results. Conclusion. Appendix:
Derviations of (14.38 and (14.40). References. 15. Energy-Efficient
Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo).
15.5 Introduction. 15.2 System Model. 15.3 Digital Approaches. 15.4 Analog
Approaches. 15.5 Analog versus Digital. 15.6 Extension to Vector Model.
15.7 Concluding Remarks. Acknowledgments. References. 16. Sensor Data
Fusion with Application to Multitarget Tracking (R. Tharmarasa, K.
Punithakumar, T. Kirubarajan and Y. Bar-Shalom). 16.1 Introduction. 16.2
Tracking Filters. 16.3 Data Association. 16.4 Out-of-Sequence Measurements.
16.5 Results with Real Data. 16.6 Summary. References. 17. Distributed
Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and José Moura).
17.1 Introduction. 17.2 Preliminaries. 17.3 Distributed Detection. 17.4
Consensus Algorithms. 17.5 Zero-Dimension (Average) Consensus. 17.6
Consensus in Higher Dimensions. 17.7 Leader-Follower (Type) Algorithms.
17.8 Localization in Sensor Networks. 17.9 Linear System of Equations:
Distributed Algorithm. 17.10 Conclusions. References. 18. Cooperative
Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu). 18.1
Introduction. 18.2 Cooperative Relay Protocols. 18.3 SER Analysis and
Optimal Power Allocation. 18.4 Energy Efficiency in Cooperative Sensor
Networks. 18.5 Experimental Results. 18.6 Conclusions. References. 19.
Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang
Yang). 19.1 Introduction. 19.2 Theoretical Background. 19.3 Code Designs.
19.4 Applications. 19.5 Conclusions. References. 20. Network Coding for
Sensor Networks (Christina Fragouli). 20.1 Introduction. 20.2 How Can We
Implement Network Coding in a Practical Sensor Network? 20.3 Data
Collection and Coupon Collector Problem. 20.4 Distributed Storage and
Sensor Network Data Persistence. 20.5 Decentralized Operation and Untuned
Radios. 20.6 Broadcasting and Multipath Diversity. 20.7 Network, Channel
and Source Coding. 20.8 Identity-Aware Sensor Networks. 20.9 Discussion.
Acknowledgments. References. 21. Information-Theoretic Studies of Wireless
Sensor Networks (Liang-Liang Xie and P. R. Kumar). 21.1 Introduction. 21.2
Information-Theoretic Studies. 21.3 Relay Schemes. 21.4 Wireless Network
Coding. 21.5 Concluding Remarks. Acknowledgments. References. PART IV:
NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS. 22.
Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S.
Cattivelli). 22.1 Introduction. 22.2 Motivation. 22.3 Incremental Adaptive
Solutions. 22.4 Diffusion Adaptive Solutions. 22.5 Concluding Remarks.
Acknowledgments. References 23. Routing for Statistical Inference in Sensor
Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong). 23.1
Introduction. 23.2 Spatial Data Correlation. 23.3 Statistical Inference of
Markov Random Fields. 23.4 Optimal Routing for Inference with Local
Processing. 23.5 Conclusion and Future Work. 23.6 Bibliographic Notes.
References. 24. Spectral Estimation in Cognitive Radios (Behrouz
Farhang-Boroujeny). 24.1 Filter Bank Formulation of Spectral Estimators.
24.2 Polyphase Realization of Uniform Filter Banks. 24.3 Periodogram
Spectral Estimator. 24.4 Multitaper Spectral Estimator. 24.5 Filter Bank
Spectral Estimator. 24.6 Distributed Spectrum Sensing. 24.7 Discussion.
Appendix A: Effective Degree of Freedom. Appendix B: Explanation to the
Results of Table 24.1. References. 25. Nonparametric Techniques for
Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and
Kostas N. Plataniotis). 25.1 Introduction. 25.2 WLAN Positioning
Architectures. 25.3 Signal Models. 25.4 Zero-Memory Positioning. 25.5
Dynamic Positioning Systems. 25.6 Cognition and Feedback. 25.7 Tracking
Example. 25.8 Conclusions. References. 26. Reconfigurable Self-Activating
Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell). 26.1
Introduction. 26.2 Biosensors Built of Ion Channels. 26.3 Joint Input
Excitation and Concentration Classification for Biosensor. 26.4
Decentralized Deployment of Dense Network of Biosensors. 26.5 Discussion
and Extensions. References. 27. Biochemical Transport Modeling, Estimation
and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ).
27.1 Introduction. 27.2 Physical and Statistical Models. 27.3 Transport
Modeling Using Monte Carlo Approximation. 27.4 Localizing the Source(s).
27.5 Sequential Detection. 27.6 Conclusion. References. 28. Security and
Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig).
28.1 Introduction. 28.2 Security and Privacy Challenges. 28.3 Ensuring
Integrity of Measurement Process. 28.4 Availability Attacks against the
Wireless Link. 28.5 Ensuring Privacy of Routing Contexts. 28.6 Conclusion.
References. Index.
Preface (Simon Haykin and K. J. Ray Liu). Contributors. Introduction (Simon
Haykin). PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING. 1.
Wavefields. (Alfred Hanssen). 1.1 Introduction. 1.2 Harmonizable Stochastic
Processes. 1.3 Stochastic Wavefields. 1.4 Wave Dispersion. 1.5 Conclusions.
1.6 Acknowledgements. References. 2. Spatial Spectrum Estimation (Petar M.
Djuri). 2.1 Introduction. 2.2 Fundamentals. 2.3 Temporal Spectrum
Estimation. 2.4 Spatial Spectrum Estimation. 2.5 Final Remarks. References.
3. MIMO Radio Propagation (Tricia J. Willink). 3.1 Introduction. 3.2
Space-Time Propagation Environment. 3.3 Propagation Models. 3.4 Measured
Channel Characteristics. 3.5 Stationarity. 3.6 Summary. References. 4.
Robustness Issues in Sensor Array Processing (Alex B. Gershman). 4.1
Introduction. 4.2 Direction-of-Arrival Estimation. 4.3 Adaptive
Beamforming. 4.4 Conclusions. Acknowledgments. References. 5. Wireless
Communication and Sensing in Multipath Environments Using Multiantenna
Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan). 5.1 Introduction
and Overview. 5.2 Multipath Wireless Channel Modeling in Time, Frequency
and Space. 5.3 Point-to-Point MIMO Wireless Communication Systems. 5.4
Active Wireless Sensing with Wideband MIMO Transceivers. 5.5 Concluding
Remarks. References. PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF
ARRAY SIGNAL PROCESSING. 6. Implicit Training and Array Processing for
Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and
Desmond C. McLernon). 6.1 Introduction. 6.2 Classification of Implicit
Training Methods. 6.3 IT-Based Estimation for a Single User. 6.4 IT-Based
Estimation for Multiple Users Exploiting Array Processing: Continuous
Transmission. 6.5 IT-Based Estimation for Multiple Users Exploiting Array
Processing: Packet Transmission. 6.6 Open Research Problems.
Acknowledgments. References. 7. Unitary Design of Radar Waveform Diversity
Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill
Moran). 7.1 Introduction. 7.2 2 x 2 Space-Time Diversity Waveform Design.
7.3 4 x 4 Space-Time Diversity Waveform Design. 7.4 Waveform Families Based
on Kronecker Products. 7.5 Introduction to Data-Dependent Waveform Design.
7.6 3 x 3 and 6 x 6 Waveform Scheduling. 7.7 Summary. References. 8.
Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard
Hänsler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff). 8.1
Introduction. 8.2 Signal Processing in the Subband Domain. 8.3 Multichannel
Echo Cancelation. 8.4 Speaker Localization. 8.5 Beamforming. 8.6 Sensor
Calibration. 8.7 Postprocessing. 8.8 Conclusions. References. 9. Acoustic
Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc
Moonen and Ann Spriet). 9.1. Introduction. 9.2. Overview of noise reduction
techniques. 9.3. Monaural beamforming. 9.4. Binaural beamforming. 9.5.
Conclusion. 10. Undetermined Blind Source Separation Using Acoustic Arrays
(Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada). 10.1
Introduction. 10.2 Underdetermined Blind Source Separation of Speeches in
Reverberant Environments. 10.3 Sparseness of Speech Sources. 10.4 Binary
Mask Approach to Underdetermined BSS. 10.5 MAP-Based Two-Stage Approach to
Underdetermined BSS. 10.6 Experimental Comparison with Binary Mask Approach
and MAP-Based Two-Stage Approach. 10.7 Concluding Remarks. References. 11.
Array Processing in Astronomy (Douglas C.-J. Bock). 11.1 Introduction. 11.2
Correlation Arrays. 11.3 Aperture Plane Phased Arrays. 11.4 Future
Directions. 11.5 Conclusion. References. 12. Digital 3D/4D Ultrasound
Imaging Array (Stergios Stergiopoulos). 12.1 Background. 12.2 Next
Generation 3D/4D Ultrasound Imaging Technology. 12.3 Computing Architecture
and Implementation Issues. 12.4 An Experimental Planar Array Ultrasound
Imaging System. 12.5 Conclusion. References. PART III: FUNDAMENTAL ISSUES
IN DISTRIBUTED SENSOR NETWORKS. 13. Self-Localization of Sensor Networks
(Josh N. Ash and Randolph L. Moses). 13.1 Introduction. 13.2 Measurement
Types and Performance Bounds. 13.3 Localization Algorithms. 13.4 Relative
and Transformation Error Decomposition. 13.5 Conclusions. References. 14.
Multitarget Tracking and Classification in Collaborative Sensor Networks
via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang). 14.1
Introduction. 14.2 System Description and Problem Formulation. 14.3
Sequential Monte Carlo Methods. 14.4 Joint Single-Target Tracking and
Classification. 14.5 Multiple-Target Tracking and Classification. 14.6
Sensor Selection. 14.7 Simulation Results. Conclusion. Appendix:
Derviations of (14.38 and (14.40). References. 15. Energy-Efficient
Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo).
15.5 Introduction. 15.2 System Model. 15.3 Digital Approaches. 15.4 Analog
Approaches. 15.5 Analog versus Digital. 15.6 Extension to Vector Model.
15.7 Concluding Remarks. Acknowledgments. References. 16. Sensor Data
Fusion with Application to Multitarget Tracking (R. Tharmarasa, K.
Punithakumar, T. Kirubarajan and Y. Bar-Shalom). 16.1 Introduction. 16.2
Tracking Filters. 16.3 Data Association. 16.4 Out-of-Sequence Measurements.
16.5 Results with Real Data. 16.6 Summary. References. 17. Distributed
Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and José Moura).
17.1 Introduction. 17.2 Preliminaries. 17.3 Distributed Detection. 17.4
Consensus Algorithms. 17.5 Zero-Dimension (Average) Consensus. 17.6
Consensus in Higher Dimensions. 17.7 Leader-Follower (Type) Algorithms.
17.8 Localization in Sensor Networks. 17.9 Linear System of Equations:
Distributed Algorithm. 17.10 Conclusions. References. 18. Cooperative
Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu). 18.1
Introduction. 18.2 Cooperative Relay Protocols. 18.3 SER Analysis and
Optimal Power Allocation. 18.4 Energy Efficiency in Cooperative Sensor
Networks. 18.5 Experimental Results. 18.6 Conclusions. References. 19.
Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang
Yang). 19.1 Introduction. 19.2 Theoretical Background. 19.3 Code Designs.
19.4 Applications. 19.5 Conclusions. References. 20. Network Coding for
Sensor Networks (Christina Fragouli). 20.1 Introduction. 20.2 How Can We
Implement Network Coding in a Practical Sensor Network? 20.3 Data
Collection and Coupon Collector Problem. 20.4 Distributed Storage and
Sensor Network Data Persistence. 20.5 Decentralized Operation and Untuned
Radios. 20.6 Broadcasting and Multipath Diversity. 20.7 Network, Channel
and Source Coding. 20.8 Identity-Aware Sensor Networks. 20.9 Discussion.
Acknowledgments. References. 21. Information-Theoretic Studies of Wireless
Sensor Networks (Liang-Liang Xie and P. R. Kumar). 21.1 Introduction. 21.2
Information-Theoretic Studies. 21.3 Relay Schemes. 21.4 Wireless Network
Coding. 21.5 Concluding Remarks. Acknowledgments. References. PART IV:
NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS. 22.
Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S.
Cattivelli). 22.1 Introduction. 22.2 Motivation. 22.3 Incremental Adaptive
Solutions. 22.4 Diffusion Adaptive Solutions. 22.5 Concluding Remarks.
Acknowledgments. References 23. Routing for Statistical Inference in Sensor
Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong). 23.1
Introduction. 23.2 Spatial Data Correlation. 23.3 Statistical Inference of
Markov Random Fields. 23.4 Optimal Routing for Inference with Local
Processing. 23.5 Conclusion and Future Work. 23.6 Bibliographic Notes.
References. 24. Spectral Estimation in Cognitive Radios (Behrouz
Farhang-Boroujeny). 24.1 Filter Bank Formulation of Spectral Estimators.
24.2 Polyphase Realization of Uniform Filter Banks. 24.3 Periodogram
Spectral Estimator. 24.4 Multitaper Spectral Estimator. 24.5 Filter Bank
Spectral Estimator. 24.6 Distributed Spectrum Sensing. 24.7 Discussion.
Appendix A: Effective Degree of Freedom. Appendix B: Explanation to the
Results of Table 24.1. References. 25. Nonparametric Techniques for
Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and
Kostas N. Plataniotis). 25.1 Introduction. 25.2 WLAN Positioning
Architectures. 25.3 Signal Models. 25.4 Zero-Memory Positioning. 25.5
Dynamic Positioning Systems. 25.6 Cognition and Feedback. 25.7 Tracking
Example. 25.8 Conclusions. References. 26. Reconfigurable Self-Activating
Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell). 26.1
Introduction. 26.2 Biosensors Built of Ion Channels. 26.3 Joint Input
Excitation and Concentration Classification for Biosensor. 26.4
Decentralized Deployment of Dense Network of Biosensors. 26.5 Discussion
and Extensions. References. 27. Biochemical Transport Modeling, Estimation
and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ).
27.1 Introduction. 27.2 Physical and Statistical Models. 27.3 Transport
Modeling Using Monte Carlo Approximation. 27.4 Localizing the Source(s).
27.5 Sequential Detection. 27.6 Conclusion. References. 28. Security and
Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig).
28.1 Introduction. 28.2 Security and Privacy Challenges. 28.3 Ensuring
Integrity of Measurement Process. 28.4 Availability Attacks against the
Wireless Link. 28.5 Ensuring Privacy of Routing Contexts. 28.6 Conclusion.
References. Index.
Haykin). PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING. 1.
Wavefields. (Alfred Hanssen). 1.1 Introduction. 1.2 Harmonizable Stochastic
Processes. 1.3 Stochastic Wavefields. 1.4 Wave Dispersion. 1.5 Conclusions.
1.6 Acknowledgements. References. 2. Spatial Spectrum Estimation (Petar M.
Djuri). 2.1 Introduction. 2.2 Fundamentals. 2.3 Temporal Spectrum
Estimation. 2.4 Spatial Spectrum Estimation. 2.5 Final Remarks. References.
3. MIMO Radio Propagation (Tricia J. Willink). 3.1 Introduction. 3.2
Space-Time Propagation Environment. 3.3 Propagation Models. 3.4 Measured
Channel Characteristics. 3.5 Stationarity. 3.6 Summary. References. 4.
Robustness Issues in Sensor Array Processing (Alex B. Gershman). 4.1
Introduction. 4.2 Direction-of-Arrival Estimation. 4.3 Adaptive
Beamforming. 4.4 Conclusions. Acknowledgments. References. 5. Wireless
Communication and Sensing in Multipath Environments Using Multiantenna
Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan). 5.1 Introduction
and Overview. 5.2 Multipath Wireless Channel Modeling in Time, Frequency
and Space. 5.3 Point-to-Point MIMO Wireless Communication Systems. 5.4
Active Wireless Sensing with Wideband MIMO Transceivers. 5.5 Concluding
Remarks. References. PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF
ARRAY SIGNAL PROCESSING. 6. Implicit Training and Array Processing for
Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and
Desmond C. McLernon). 6.1 Introduction. 6.2 Classification of Implicit
Training Methods. 6.3 IT-Based Estimation for a Single User. 6.4 IT-Based
Estimation for Multiple Users Exploiting Array Processing: Continuous
Transmission. 6.5 IT-Based Estimation for Multiple Users Exploiting Array
Processing: Packet Transmission. 6.6 Open Research Problems.
Acknowledgments. References. 7. Unitary Design of Radar Waveform Diversity
Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill
Moran). 7.1 Introduction. 7.2 2 x 2 Space-Time Diversity Waveform Design.
7.3 4 x 4 Space-Time Diversity Waveform Design. 7.4 Waveform Families Based
on Kronecker Products. 7.5 Introduction to Data-Dependent Waveform Design.
7.6 3 x 3 and 6 x 6 Waveform Scheduling. 7.7 Summary. References. 8.
Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard
Hänsler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff). 8.1
Introduction. 8.2 Signal Processing in the Subband Domain. 8.3 Multichannel
Echo Cancelation. 8.4 Speaker Localization. 8.5 Beamforming. 8.6 Sensor
Calibration. 8.7 Postprocessing. 8.8 Conclusions. References. 9. Acoustic
Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc
Moonen and Ann Spriet). 9.1. Introduction. 9.2. Overview of noise reduction
techniques. 9.3. Monaural beamforming. 9.4. Binaural beamforming. 9.5.
Conclusion. 10. Undetermined Blind Source Separation Using Acoustic Arrays
(Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada). 10.1
Introduction. 10.2 Underdetermined Blind Source Separation of Speeches in
Reverberant Environments. 10.3 Sparseness of Speech Sources. 10.4 Binary
Mask Approach to Underdetermined BSS. 10.5 MAP-Based Two-Stage Approach to
Underdetermined BSS. 10.6 Experimental Comparison with Binary Mask Approach
and MAP-Based Two-Stage Approach. 10.7 Concluding Remarks. References. 11.
Array Processing in Astronomy (Douglas C.-J. Bock). 11.1 Introduction. 11.2
Correlation Arrays. 11.3 Aperture Plane Phased Arrays. 11.4 Future
Directions. 11.5 Conclusion. References. 12. Digital 3D/4D Ultrasound
Imaging Array (Stergios Stergiopoulos). 12.1 Background. 12.2 Next
Generation 3D/4D Ultrasound Imaging Technology. 12.3 Computing Architecture
and Implementation Issues. 12.4 An Experimental Planar Array Ultrasound
Imaging System. 12.5 Conclusion. References. PART III: FUNDAMENTAL ISSUES
IN DISTRIBUTED SENSOR NETWORKS. 13. Self-Localization of Sensor Networks
(Josh N. Ash and Randolph L. Moses). 13.1 Introduction. 13.2 Measurement
Types and Performance Bounds. 13.3 Localization Algorithms. 13.4 Relative
and Transformation Error Decomposition. 13.5 Conclusions. References. 14.
Multitarget Tracking and Classification in Collaborative Sensor Networks
via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang). 14.1
Introduction. 14.2 System Description and Problem Formulation. 14.3
Sequential Monte Carlo Methods. 14.4 Joint Single-Target Tracking and
Classification. 14.5 Multiple-Target Tracking and Classification. 14.6
Sensor Selection. 14.7 Simulation Results. Conclusion. Appendix:
Derviations of (14.38 and (14.40). References. 15. Energy-Efficient
Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo).
15.5 Introduction. 15.2 System Model. 15.3 Digital Approaches. 15.4 Analog
Approaches. 15.5 Analog versus Digital. 15.6 Extension to Vector Model.
15.7 Concluding Remarks. Acknowledgments. References. 16. Sensor Data
Fusion with Application to Multitarget Tracking (R. Tharmarasa, K.
Punithakumar, T. Kirubarajan and Y. Bar-Shalom). 16.1 Introduction. 16.2
Tracking Filters. 16.3 Data Association. 16.4 Out-of-Sequence Measurements.
16.5 Results with Real Data. 16.6 Summary. References. 17. Distributed
Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and José Moura).
17.1 Introduction. 17.2 Preliminaries. 17.3 Distributed Detection. 17.4
Consensus Algorithms. 17.5 Zero-Dimension (Average) Consensus. 17.6
Consensus in Higher Dimensions. 17.7 Leader-Follower (Type) Algorithms.
17.8 Localization in Sensor Networks. 17.9 Linear System of Equations:
Distributed Algorithm. 17.10 Conclusions. References. 18. Cooperative
Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu). 18.1
Introduction. 18.2 Cooperative Relay Protocols. 18.3 SER Analysis and
Optimal Power Allocation. 18.4 Energy Efficiency in Cooperative Sensor
Networks. 18.5 Experimental Results. 18.6 Conclusions. References. 19.
Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang
Yang). 19.1 Introduction. 19.2 Theoretical Background. 19.3 Code Designs.
19.4 Applications. 19.5 Conclusions. References. 20. Network Coding for
Sensor Networks (Christina Fragouli). 20.1 Introduction. 20.2 How Can We
Implement Network Coding in a Practical Sensor Network? 20.3 Data
Collection and Coupon Collector Problem. 20.4 Distributed Storage and
Sensor Network Data Persistence. 20.5 Decentralized Operation and Untuned
Radios. 20.6 Broadcasting and Multipath Diversity. 20.7 Network, Channel
and Source Coding. 20.8 Identity-Aware Sensor Networks. 20.9 Discussion.
Acknowledgments. References. 21. Information-Theoretic Studies of Wireless
Sensor Networks (Liang-Liang Xie and P. R. Kumar). 21.1 Introduction. 21.2
Information-Theoretic Studies. 21.3 Relay Schemes. 21.4 Wireless Network
Coding. 21.5 Concluding Remarks. Acknowledgments. References. PART IV:
NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS. 22.
Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S.
Cattivelli). 22.1 Introduction. 22.2 Motivation. 22.3 Incremental Adaptive
Solutions. 22.4 Diffusion Adaptive Solutions. 22.5 Concluding Remarks.
Acknowledgments. References 23. Routing for Statistical Inference in Sensor
Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong). 23.1
Introduction. 23.2 Spatial Data Correlation. 23.3 Statistical Inference of
Markov Random Fields. 23.4 Optimal Routing for Inference with Local
Processing. 23.5 Conclusion and Future Work. 23.6 Bibliographic Notes.
References. 24. Spectral Estimation in Cognitive Radios (Behrouz
Farhang-Boroujeny). 24.1 Filter Bank Formulation of Spectral Estimators.
24.2 Polyphase Realization of Uniform Filter Banks. 24.3 Periodogram
Spectral Estimator. 24.4 Multitaper Spectral Estimator. 24.5 Filter Bank
Spectral Estimator. 24.6 Distributed Spectrum Sensing. 24.7 Discussion.
Appendix A: Effective Degree of Freedom. Appendix B: Explanation to the
Results of Table 24.1. References. 25. Nonparametric Techniques for
Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and
Kostas N. Plataniotis). 25.1 Introduction. 25.2 WLAN Positioning
Architectures. 25.3 Signal Models. 25.4 Zero-Memory Positioning. 25.5
Dynamic Positioning Systems. 25.6 Cognition and Feedback. 25.7 Tracking
Example. 25.8 Conclusions. References. 26. Reconfigurable Self-Activating
Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell). 26.1
Introduction. 26.2 Biosensors Built of Ion Channels. 26.3 Joint Input
Excitation and Concentration Classification for Biosensor. 26.4
Decentralized Deployment of Dense Network of Biosensors. 26.5 Discussion
and Extensions. References. 27. Biochemical Transport Modeling, Estimation
and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ).
27.1 Introduction. 27.2 Physical and Statistical Models. 27.3 Transport
Modeling Using Monte Carlo Approximation. 27.4 Localizing the Source(s).
27.5 Sequential Detection. 27.6 Conclusion. References. 28. Security and
Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig).
28.1 Introduction. 28.2 Security and Privacy Challenges. 28.3 Ensuring
Integrity of Measurement Process. 28.4 Availability Attacks against the
Wireless Link. 28.5 Ensuring Privacy of Routing Contexts. 28.6 Conclusion.
References. Index.