Foundations and Applications of Sensor Management
Contributor(s): Hero, Alfred O [editor.1 ] | Casta��n, David A [editor.1 ] | [editor.1 ] | [editor.2 ] | .
Material type:
BookBoston, MA : Springer US, 2008. Description: XVIII, 310 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780387498195.Subject(s): Engineering. 0 | Coding theory. 0 | Control engineering. 0 | Robotics. 0 | Mechatronics. 0 | Electrical engineering.14 | Engineering.24 | Signal, Image and Speech Processing.24 | Communications Engineering, Networks.24 | Control, Robotics, Mechatronics.24 | Coding and Information Theory.24 | Electrical Engineering.1DDC classification: 621.382 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| PK Kelkar Library, IIT Kanpur | Available | EBKS000480 |
Overview of Book -- Stochastic Control Theory for Sensor Management -- Information Theoretic Approaches to Sensor Management -- Joint Multi-Target Particle Filtering -- Pomdp Approximation Using Simulation and Heuristics -- Multi-Armed Bandit Problems -- Application of Multi-Armed Bandits to Sensor Management -- Active Learning and Sampling -- Plan-In-Advance Active Learning 0f Classifiers -- Application of Sensor Scheduling Concepts to Radar -- Defense Applications -- Appendices.
Foundations and Applications of Sensor Management presents the emerging theory of sensor management with applications to real-world examples such as landmine detection, adaptive signal and image sampling, multi-target tracking, and radar waveform scheduling. It is written by leading experts in the field for a diverse engineering audience ranging from signal processing, to automatic control, statistics, and machine learning. The level of treatment of the book is tutorial and self-contained. The chapters of the book follow a logical development from theoretical foundations to approximate approaches and ending with applications. The coverage includes the following topics: stochastic control foundations of sensor management; multi-armed bandits and their connections to sensor management; information-theoretic approaches; managed sensing for multi-target tracking; approximation methods based on embedded simulation; active learning for classification and sampling; and waveform scheduling for radar. An appendix is included to provide essential background on topics the reader may not have encountered as a first-year graduate student: Markov decision processes; information theory; and stopping times. Foundations and Applications of Sensor Management is an important reference for signal processing and control engineers and researchers as well as machine learning application developers. 0
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