Handbook on array processing and sensor networks

Handbook on array processing and sensor networks

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 p...

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Detalles Bibliográficos
Autor principal: Haykin, Simon S., 1931- (-)
Otros Autores: Liu, K. J. Ray, 1961-
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, N.J. : John Wiley & Sons 2009.
Edición:1st edition
Colección:Adaptive and learning systems for signal processing, communications and control series ; 64
Materias:
Sensor networks.
Antenna arrays.
Array processors.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628303806719
Tabla de Contenidos:
  • 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 H Ansler, 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 Jos A A 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.

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