000 | 16045nam a2202053 i 4500 | ||
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001 | 5493575 | ||
003 | IEEE | ||
005 | 20200421114118.0 | ||
006 | m o d | ||
007 | cr |n||||||||| | ||
008 | 100812t20152009njua obd 001 0 eng d | ||
020 |
_a9780470487068 _qelectronic |
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020 |
_z9780470371763 _qprint |
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020 |
_z9780470487051 _qelectronic |
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020 |
_z0470487054 _qelectronic |
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020 |
_z0470487062 _qelectronic |
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024 | 7 |
_a10.1002/9780470487068 _2doi |
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035 | _a(CaBNVSL)mat05493575 | ||
035 | _a(IDAMS)0b000064812a470e | ||
040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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050 | 4 |
_aTK7872.D48 _bH39 2009eb |
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082 | 0 | 4 |
_a621.382/4 _222 |
245 | 0 | 0 |
_aHandbook on array processing and sensor networks / _c[edited by] Simon Haykin, K.J. Ray Liu. |
264 | 1 |
_a[Piscataway, New Jersey] : _bIEEE, _cc2009 |
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264 | 2 |
_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2010] |
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300 |
_a1 PDF (xviii, 904 pages) : _billustrations. |
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336 |
_atext _2rdacontent |
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337 |
_aelectronic _2isbdmedia |
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_aonline resource _2rdacarrier |
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490 | 1 |
_aAdaptive and learning systems for signal processing, communications and control series ; _v64 |
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504 | _aIncludes bibliographical references. | ||
505 | 0 | _aPreface (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). | |
505 | 8 | _a7.1 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. | |
505 | 8 | _a13. 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. | |
505 | 8 | _a18.4 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. | |
505 | 8 | _a24.3 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. | |
506 | 1 | _aRestricted to subscribers or individual electronic text purchasers. | |
530 | _aAlso available in print. | ||
538 | _aMode of access: World Wide Web | ||
588 | _aDescription based on PDF viewed 12/21/2015. | ||
650 | 0 | _aSensor networks. | |
650 | 0 | _aAntenna arrays. | |
650 | 0 | _aArray processors. | |
655 | 0 | _aElectronic books. | |
695 | _aAcoustics | ||
695 | _aAd hoc networks | ||
695 | _aAdaptive systems | ||
695 | _aArray signal processing | ||
695 | _aArrays | ||
695 | _aAuditory system | ||
695 | _aBaseband | ||
695 | _aBiological system modeling | ||
695 | _aBiomedical measurements | ||
695 | _aBiomembranes | ||
695 | _aBiosensors | ||
695 | _aBlind source separation | ||
695 | _aChannel coding | ||
695 | _aChannel estimation | ||
695 | _aClutter | ||
695 | _aCognitive radio | ||
695 | _aCollaboration | ||
695 | _aComputational modeling | ||
695 | _aCorrelation | ||
695 | _aCovariance matrix | ||
695 | _aDecoding | ||
695 | _aDelay | ||
695 | _aDirection of arrival estimation | ||
695 | _aDiscrete Fourier transforms | ||
695 | _aDispersion | ||
695 | _aDistortion measurement | ||
695 | _aEncoding | ||
695 | _aEncryption | ||
695 | _aEnergy consumption | ||
695 | _aEquations | ||
695 | _aEstimation | ||
695 | _aFading | ||
695 | _aFilter banks | ||
695 | _aFourier transforms | ||
695 | _aFrequency domain analysis | ||
695 | _aFrequency estimation | ||
695 | _aGames | ||
695 | _aHearing aids | ||
695 | _aImage resolution | ||
695 | _aImaging | ||
695 | _aImmune system | ||
695 | _aIndexes | ||
695 | _aInterference | ||
695 | _aJoints | ||
695 | _aKalman filters | ||
695 | _aLead | ||
695 | _aLearning systems | ||
695 | _aLeast squares approximation | ||
695 | _aLipidomics | ||
695 | _aMIMO | ||
695 | _aMIMO radio propagation | ||
695 | _aMarkov processes | ||
695 | _aMathematical model | ||
695 | _aMeasurement | ||
695 | _aMedia Access Protocol | ||
695 | _aMicrophones | ||
695 | _aMinimization | ||
695 | _aMobile communication | ||
695 | _aModulation | ||
695 | _aMonitoring | ||
695 | _aMoon | ||
695 | _aNarrowband | ||
695 | _aNetwork coding | ||
695 | _aNetwork topology | ||
695 | _aNoise | ||
695 | _aNoise measurement | ||
695 | _aNoise reduction | ||
695 | _aNumerical models | ||
695 | _aPeer to peer computing | ||
695 | _aPollution measurement | ||
695 | _aPosition measurement | ||
695 | _aPrivacy | ||
695 | _aProbes | ||
695 | _aProtocols | ||
695 | _aPrototypes | ||
695 | _aQuantization | ||
695 | _aRadar | ||
695 | _aRadar antennas | ||
695 | _aRadar tracking | ||
695 | _aRandom processes | ||
695 | _aRate-distortion | ||
695 | _aReal time systems | ||
695 | _aReceivers | ||
695 | _aReceiving antennas | ||
695 | _aRelays | ||
695 | _aRobustness | ||
695 | _aRouting | ||
695 | _aSections | ||
695 | _aSensor arrays | ||
695 | _aSensor fusion | ||
695 | _aSensors | ||
695 | _aSignal processing | ||
695 | _aSignal processing algorithms | ||
695 | _aSignal to noise ratio | ||
695 | _aSource coding | ||
695 | _aSpectral analysis | ||
695 | _aSpeech | ||
695 | _aSpeech enhancement | ||
695 | _aStochastic processes | ||
695 | _aTarget tracking | ||
695 | _aTemperature measurement | ||
695 | _aTemperature sensors | ||
695 | _aThree dimensional displays | ||
695 | _aTime frequency analysis | ||
695 | _aTime measurement | ||
695 | _aTransceivers | ||
695 | _aTransmitters | ||
695 | _aUltrasonic imaging | ||
695 | _aWireless LAN | ||
695 | _aWireless communication | ||
695 | _aWireless networks | ||
695 | _aWireless sensor networks | ||
695 | _aYttrium | ||
695 | _aaperture plane phased arrays | ||
695 | _aarray processing in astronomy in radio astronomy | ||
695 | _alocalization algorithms | ||
695 | _amaximum entropy method (MEM) deconvolution method finding a model image with maximum entropy | ||
695 | _ameasured channel characteristics | ||
695 | _apropagation models, marketing of MIMO and assumption of uncorrelated fading | ||
695 | _arelative and transformation error decomposition | ||
695 | _aselflocalization of sensor networks | ||
700 | 1 | _aLiu, K. J. Ray. | |
700 | 1 | _aHaykin, Simon S. | |
710 | 2 |
_aIEEE Xplore (Online Service), _edistributor. |
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710 | 2 |
_aJohn Wiley & Sons, _epublisher. |
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776 | 0 | 8 |
_iPrint version: _z9780470371763 |
830 | 0 |
_aAdaptive and learning systems for signal processing, communications and control series ; _v64 |
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856 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5493575 |
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942 | _cEBK | ||
999 |
_c59648 _d59648 |