Hand Book on Array Processing and Sensor Networks
By: Haykin, Simon.
Contributor(s): Liu, K J Ray.
Material type:
BookPublisher: New Delhi Wiley India Pvt. Ltd. India 2015,c2009Description: 904.ISBN: 9788126556076.Subject(s): ElectronicsDDC classification: 621.382 4
| Item type | Current location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Books
|
BSDU Knowledge Resource Center, Jaipur | Reference | 621.382 4 HAY (Browse shelf) | Not For Loan | 001930 |
The major goal of the Handbook on Sensor and Array Processing is to collect tutorial articles on recent advancements and state-of-the-art results by providing a comprehensive overview of sensor and array processing. It will cover fundamental principles as well as applications. It will be the first such book on this subject. The handbook will feature some of the most prominent researchers from different centers in North America and Europe to address all the important topics that we consider to be important for making the handbook highly successful; this point is well borne out by the list of contents.
Contents
Preface
Contributors.
Introduction
Part I: Fundamental Issues in Array Signal Processing.
1. Wavefields.
1.1 Introduction.
1.2 Harmonizable Stochastic Processes.
1.3 Stochastic Wavefields.
1.4 Wave Dispersion.
1.5 Conclusions.
1.6 Acknowledgements.
2. Spatial Spectrum Estimation
2.1Â Introduction.
2.2 Fundamentals.
2.3 Temporal Spectrum Estimation.
2.4 Spatial Spectrum Estimation.
2.5 Final Remarks.
3. MIMO Radio Propagation
3.1 Introduction.
3.2 Space-Time Propagation Environment.
3.3 Propagation Models.
3.4 Measured Channel Characteristics.
3.5 Stationarity.
3.6 Summary.
4. Robustness Issues in Sensor Array Processing
4.1 Introduction.
4.2 Direction-of-Arrival Estimation.
4.3 Adaptive Beamforming.
4.4 Conclusions.
5. Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers
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.
Part II: Novel Techniques for and Applications of Array Signal Processing.
6. Implicit Training and Array Processing for Digital Communication Systems
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.
7. Unitary Design of Radar Waveform Diversity Sets
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.
8. Acoustic Array Processing for Speech Enhancement
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.
9. Acoustic Beamforming for Hearing Aid Applications
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
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.
11. Array Processing in Astronomy
11.1 Introduction.
11.2 Correlation Arrays.
11.3 Aperture Plane Phased Arrays.
11.4 Future Directions.
11.5 Conclusion.
12. Digital 3D/4D Ultrasound Imaging Array
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.
Part III: Fundamental Issues in Distributed Sensor Networks.
13. Self-Localization of Sensor Networks
13.1 Introduction.
13.2 Measurement Types and Performance Bounds.
13.3 Localization Algorithms.
13.4 Relative and Transformation Error Decomposition.
13.5 Conclusions.
14. Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo
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.
15. Energy-Efficient Decentralized Estimation
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.
16. Sensor Data Fusion with Application to Multitarget Tracking
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.
17. Distributed Algorithms in Sensor Networks
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.
18. Cooperative Sensor Communications
18.1 Introduction.
18.2 Cooperative Relay Protocols.
18.3 SERÂ Analysis and Optimal Power Allocation.
18.4 Energy Efficiency in Cooperative Sensor Networks.
18.5 Experimental Results.
18.6 Conclusions.
19. Distributed Source Coding
19.1 Introduction.
19.2 Theoretical Background.
19.3 Code Designs.
19.4 Applications.
19.5 Conclusions.
20. Network Coding for Sensor Networks
20.1 Introduction.
20.2Â 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.
21. Information-Theoretic Studies of Wireless Sensor Networks
21.1 Introduction.
21.2 Information-Theoretic Studies.
21.3 Relay Schemes.
21.4 Wireless Network Coding.
21.5 Concluding Remarks.
Part IV: Novel Techniques for and Applications of Distributed Sensor Networks.
22. Distributed Adaptive Learning Mechanisms
22.1 Introduction.
22.2 Motivation.
22.3 Incremental Adaptive Solutions.
22.4 Diffusion Adaptive Solutions.
22.5 Concluding Remarks.
23. Routing for Statistical Inference in Sensor Networks
23.1Â Introduction.
23.2Â Spatial Data Correlation.
23.3Â 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.
24. Spectral Estimation in Cognitive Radios
24.1 Filter Bank Formulation of Spectral Estimators.
24.2 Polyphase Realization of Uniform Filter Banks.
24.3 Periodogram Spectral Estimator.
24.4Â Multitaper Spectral Estimator.
24.5 Filter Bank Spectral Estimator.
24.6 Distributed Spectrum Sensing.
24.7 Discussion.
25. Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks
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.
26. Reconfigurable Self-Activating Ion-Channel-Based Biosensors
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.
27. Biochemical Transport Modeling, Estimation and Detection in Realistic Environments
27.1Â 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.
28. Security and Privacy for Sensor Networks
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.
There are no comments for this item.