- ISBN: 9780470371763 | 0470371765
- Cover: Hardcover
- Copyright: 1/12/2010
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 | |
Wavefields | |
Introduction | |
Harmonizable Stochastic Processes | |
Stochastic Wavefields | |
Wave Dispersion | |
Conclusions | |
Acknowledgements | |
Spatial Spectrum Estimation | |
Introduction | |
Fundamentals | |
Temporal spectrum estimation | |
Non-parametric methods | |
Spatial spectrum estimation | |
The model | |
Non-parametric methods | |
Parametric methods | |
Estimation of the number of impinging signals | |
Final remarks | |
MIMO Radio Propagation | |
Introduction | |
The space-time propagation environment | |
Propagation models | |
Measured channel characteristics | |
Stationarity | |
Robustness Issues in Sensor Array Processing | |
Robustness Issues in Sensor Array Processing | |
Direction-of-arrival estimation | |
Adaptive beamforming | |
Conclusions | |
Wireless Communication and Sensing in Multipath Environments Using Multi Antenna Transceivers | |
Overview | |
Multipath Wireless Channel Modeling in Time, Frequency and Space | |
MIMO Wireless Communication Systems | |
Active Wireless Sensing | |
Directions for Future Research | |
Concluding Remarks | |
Implicit Training and Array Processing for Digital Communications Systems | |
Introduction | |
Classification of Implicit Training Methods | |
IT-Based Estimation for a Single User | |
IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission | |
IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission | |
Open Research Problems | |
References | |
Unitary Design of Radar Waveform Diversity Sets | |
Introduction | |
2x2 Space-Time Diversity Waveform Design | |
4x4 Space-Time Diversity Waveform Design | |
Waveform Families Based on Kronecker Products | |
Introduction to Data Dependent Waveform Design | |
3x3 and 6x6 Waveform Scheduling | |
Summary | |
Acoustic Array Processing for Speech Enhancement | |
Introduction | |
Signal Processing in the Subband Domain | |
Multi-Channel Echo Cancelation | |
Speaker Localization | |
Beamforming | |
Sensor Calibration | |
Postprocessing | |
Conclusions | |
References | |
Acoustic Beamforming for Hearing Aid Applications | |
Introduction | |
Overview of Noise Reduction Techniques | |
Monaural Beamforming | |
Binaural Beamforming | |
Conclusion | |
Undetermined Blind Source Separation using Acoustic Arrays | |
Introduction | |
Underdetermined Blind Source Separation of Speeches in Reverberant Environments | |
Sparseness of Speech Sources | |
Binary Mask Approach to Underdetermined BSS | |
MAP-Based Two-Stage Approach to Underdetermined BSS | |
Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach | |
Concluding Remarks | |
References | |
Index | |
Array Processing in Astronomy (Douglas C.-JBock) | |
Introduction | |
Correlation Arrays | |
Aperture Plane Phased Arrays | |
Future Directions | |
Conclusion | |
Digital 3D/4D Ultrasound Imaging Technology | |
Background | |
Next Generation 3D/4D Ultrasound Imaging Technology | |
Computing Architecture and Implementation Issues | |
An Experimental Planar Array Ultrasound Imaging System | |
Conclusion | |
Reference | |
Self-Localization of Sensor Networks | |
Introduction | |
The Self-localization Problem | |
Algorithm Classifications | |
Localization Algorithms | |
Relative and Transformation Error Decomposition | |
Conclusions | |
Multi-Target Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo | |
Introduction | |
System Description and Problem Formulation | |
Sequential Monte Carlo (SMC) Methods | |
Joint Single Target Tracking And Classification | |
Multiple Target Tracking and Classification | |
Sensor Selection | |
Simulation Results | |
Conclusion | |
Energy-Efficient Decentralized Estimation | |
Motivation and Introduction | |
Distributed Estimation: Digital Approaches | |
Distributed Estimation: Analog Approaches | |
Distributed Anti-jammer Sensing via Game Theory | |
Future research discussion | |
Sensor Data Fusion with Application to Multi-Target Tracking | |
Introduction | |
Tracking Filters | |
Data Association | |
Out-of-Sequence Measurements | |
Results with Real Data | |
Distributed Algorithms in Sensor Networks | |
Introduction | |
Preliminaries | |
Distributed Detection | |
Consensus Algorithms | |
Zero-Dimension (Average) Consensus | |
Consensus in Higher Dimensions | |
Leader-Follower (type) Algorithms | |
Localization in Sensor Networks | |
Linear System of Equations: Distributed Algorithm | |
Conclusions | |
Cooperative Sensor Communications | |
Introduction | |
Cooperative Relay Protocols | |
Performance Analysis and Optimal Power Allocation | |
Energy Efficiency in Cooperative Sensor Networks | |
Experimental Results | |
Conclusions | |
Distributed Source Coding | |
Introduction | |
Theoretical background | |
Code designs | |
Applications | |
Conclusions | |
Network Coding for Sensor Networks | |
I Introduction | |
II How can we implement network coding in a practical sensor network | |
III Data collection and the coupon collectors problem | |
IV Distributed storage and sensor network data persistence | |
V Decentralized operation and untuned radios | |
VI Broadcasting and multipath diversity | |
VII Network, channel and source coding | |
VIII Identity aware sensor networks | |
IX Discussion | |
Information-Theoretic Studies of Wireless Sensor Networks | |
Information-Theoretic Studies of Wireless Sensor Networks | |
Information-theoretic studies | |
Relay schemes | |
Wireless network coding | |
Concluding remarks | |
Distributed Adaptive Learning Mechanisms | |
Introduction | |
Motivation | |
Incremental Adaptive Solutions | |
Diffusion Adaptive Solutions | |
Concluding Remarks | |
References | |
Routing for Statistical Inference in Sensor Networks | |
Introduction | |
Spatial Data Correlation | |
Statistical Inference of Markov Random Fields | |
Optimal Routing for Inference with Local Processing | |
Conclusion and Future Work 2 | |
Spectrum Estimation in Cognitive Radios | |
I Filter Bank Formulation of Spectral Estimators | |
II Polyphase Realization of Uniform Filter Banks | |
III Periodogram Spectral Estimator | |
IV Multitaper Spectral Estimator | |
V Filter Bank Spectral Estimator | |
VI Distributed Spectrum Sensing | |
VII Discussion | |
Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks | |
Introduction | |
WLAN Positioning Architectures | |
Signal Models | |
Zero-Memory Positioning | |
Dynamic Positioning Systems | |
Cognition & Feedback | |
Tracking Example | |
Conclusions | |
References | |
Reconfigurable Self-Activating Ion-Channel Based Biosensors: Signal Processing and Networking via the Theory of Global Games | |
Introduction | |
Biosensors built of ion channels | |
Joint Input Excitation and Concentration Classification of Biosensor | |
Decentralized Deployment of Dense Network of Biosensors | |
Discussion and Extensions | |
Biochemical Transport Modeling, Estimation and Detection in Realistic Environments | |
Introduction | |
Physical, statistical and numerical models | |
Localizing the sources | |
Sequential Detection | |
Conclusion | |
Security and Privacy for Sensor Networks | |
Introduction2 | |
Security and Privacy Challenges | |
Ensuring the Integrity of the Measurement Process | |
Availability Attacks against the Wireless Link | |
Ensuring Privacy of Routing Contexts | |
Conclusion | |
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