Multi-Sensor Data Fusion

Part I. Basics

1. Introduction
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2. Sensors
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3. Architecture
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Part II. Representation

4. Common Representational Format
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5. Spatial Alignment
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6. Temporal Alignment
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7. Sensor Value Normalization
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Part III. Data Fusion

8. Bayesian Inference
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9. Parameter Estimation
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10. Robust Statistics
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11. Sequential Bayesian Inference
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12. Bayesian Decision Theory
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13. Ensemble Learning
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Part IV. Sensor Management

14. Sensor Management
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Part V. Appendices

15. Software Sources
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16. Sensor Management
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DRM-restrictions

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Keywords: TECHNOLOGY & ENGINEERING / General TEC000000