Contents

Contributors

Preface

1.Complex and Hypercomplex Multidimensional Analytic Signals – The Theory and Chosen Properties

1.1. Introduction
1.2. Analytic Signals in the Complex Domain
1.3. Analytic Signals in the Hypercomplex Domain
1.4. Polar Representation of Complex and Hypercomplex Analytic Signals
1.5. Conclusions
References

2. Signal Processing by Generalized Receiver  in Wireless Communications Systems  over Fading Channels

2.1. Generalized Detector: Quaternary DS-SSMA Wireless Communications Systems
2.2. Generalized Detector: Orthogonal Space-time Block Coding
References
Appendixes

3. Exploitation of the Properties  of Communication Signals: From Non-circular Signal to Circular Signal

3.1. Introduction
3.2. Exploitation of Non-circularity
3.3. Exploitation of Cyclostationarity
3.4. Exploitation of Conjugate Symmetry
3.5. Summary
Acknowledgment
References

4. A Review on Chirp and Some Other Related Signal Processing Models

4.1. Introduction
4.2. Notations and Preliminaries
4.3. Sinusoidal Model
4.4. One Dimensional One Component Chirp Model
4.5. One Dimensional Multicomponent Chirp Model
4.6. Polynomial Phase Model
4.7. Random Amplitude Chirp Model
4.8. Sum of Sinusoidal and Chirplet Model
4.9. Harmonic Chirp Model
4.10. Two Dimensional Chirp Model
4.11. Conclusions
Acknowledgements
References

5. New Statistical Algorithms for 3D Signal Processing: The Detection of Floating Objects on an Agitated Sea Surface

5.1. Introduction
5.2. 3D Subpixel Target Detection
5.3. 3D Multipixel Target Detection
References

6. Sleep Scoring Based on Biomedical Signals: A Survey and a New Algorithm

6.1. Sleep
6.2. Physiological Factors Affecting Sleep
6.3. Sleep Stages
6.4. The Importance of Sleep Study
6.5. Automatic Sleep Stages Classification
6.6. Conclusion and Future Works
References

7.  Statistical Learning of Phase Measuring Deflectometry for Defect Detection and Classification on Specular Cab Body Surfaces

7.1. Introduction
7.2. Data Acquisition
7.3. Feature Vectors
7.4. Learning Defect Classifiers

7.5. Performance Evaluation
7.6. Results and Discussion
7.7. Real-time Visualization
7.8. Conclusions
Acknowledgements
References

8. Feature Selection from Time-Frequency Images for Change Detection

8.1. Introduction
8.2. Data Transforms
8.3. Description of the Feature Selection Methods
8.4. Data Description and Analysis
8.5. Results of the Experiments
8.6. Conclusions
Acknowledgements
References

9. Information Entropy for Image Segmentation and Registration

9.1. Information Entropy
9.2. Entropy Based Image Segmentation
9.3. Entropy Based Image Registration
9.4. Conclusions
Acknowledgements
References

10. EEG Signal Analysis with a Statistical Entropy-based Measure for Alzheimer’s Disease Detection

10.1. Context
10.2. Electroencephalography (EEG)
10.3. State-of-the-art
10.4. EEG Database Description
10.5. EEG Functional Connectivity Measures
10.6. Experimental Study and Results
10.7. Discussion and Conclusion
References

11. Artefacts Detection in EEG Signals

11.1. Introduction
11.2. Artefacts
11.3. Database
11.4. Artefacts Removal Methods	
11.5. Conclusions
References

12. BeE-nose – An In-hive Multi-gas-sensor Extension to the IndusBee 4.0 System  for Hive Air Quality Monitoring and Varroa Infestation Level Estimation

12.1. Introduction
12.2. Integrated Gas Sensors and Sensing Systems
12.3. IndusBee 4.0 In-hive Monitoring System
12.4. In-field Application and Data Acquisition
12.5. Experiments and Results
12.6. Conclusions and Future Work
References

Index