Foundations and Applications of Sensor Management: Signals and Communication Technology
Editat de Alfred Olivier Hero, David Castañón, Doug Cochran, Keith Kastellaen Limba Engleză Hardback – 15 noi 2007
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.
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 926.63 lei 6-8 săpt. | |
Springer Us – 23 noi 2010 | 926.63 lei 6-8 săpt. | |
Hardback (1) | 933.59 lei 6-8 săpt. | |
Springer Us – 15 noi 2007 | 933.59 lei 6-8 săpt. |
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Specificații
ISBN-13: 9780387278926
ISBN-10: 0387278923
Pagini: 308
Ilustrații: XVIII, 310 p.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 0.66 kg
Ediția:2008
Editura: Springer Us
Colecția Springer
Seria Signals and Communication Technology
Locul publicării:New York, NY, United States
ISBN-10: 0387278923
Pagini: 308
Ilustrații: XVIII, 310 p.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 0.66 kg
Ediția:2008
Editura: Springer Us
Colecția Springer
Seria Signals and Communication Technology
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
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.
Textul de pe ultima copertă
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.
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.
Caracteristici
Targets diverse communities by including editors and contributors who are pioneers and representatives in the area of active sensing and sensor management. Presents the theory of sensor management with applications to real world examples such as adaptive mine detection and adaptive signal and image sampling among others. Includes supplementary material: sn.pub/extras