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|a 9780387886190
|9 978-0-387-88619-0
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|a 10.1007/978-0-387-88619-0
|2 doi
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|a QA402.5-402.6
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|a MAT003000
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|a 519.6
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|a Sensors: Theory, Algorithms, and Applications
|h [electronic resource] /
|c edited by Vladimir L. Boginski, Clayton W. Commander, Panos M. Pardalos, Yinyu Ye.
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|a New York, NY :
|b Springer New York,
|c 2012.
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|a X, 242 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
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|a text file
|b PDF
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|a Springer Optimization and Its Applications,
|x 1931-6828 ;
|v 61
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|a Preface -- On Enhancing Fault Tolerance of Virtual Backbone in a Wireless Sensor Network with Unidirectional Links (R. Tiwari, M.T. Thai) -- Constrained Node Placement and Assignment in Mobile Backbone Networks (E.M. Craparo) -- Canonical Dual Solutions to Sum of Fourth-Order Polynomials Minimization Problems with Applications to Sensor Network Localization (D.Y. Gao, N. Ruan, P.M. Pardalos) -- Optimal Estimation of Multidimensional Data with Limited Measurements (W. MacKunis, J. W. Curtis, P.E.K. Berg-Yuen) -- Informational Patterns in Discrete-Time Linear-Quadratic Dynamic Games (M. Pachter, K.D. Pham) -- The Design of Dynamical Inquiring Systems: A Certainty Equivalent Formalization (L. Di Giacomo, G. Patrizi) -- Sensors in Transportation and Logistics Networks (C. Vogiatzis) -- Study of Mobile Mixed Sensing Networks in an Automotive Context (A. Chakravarthy, K. Song, J. Peraire, E. Feron) -- Navigation in Difficult Environments: Multi-Sensor Fusion Techniques (A. Soloviev, M. M. Miller) -- A Spectral Clustering Approach for Modeling Connectivity Patterns in Electroencephalogram Sensor Networks (P. Xanthopoulos, A. Arulselvan, P. M. Pardalos.).
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|a In recent years, technological advances have resulted in the rapid development of a new and exciting research direction – the interdisciplinary use of sensors for data collection, systems analysis, and monitoring. These highly calibrated sensors require precision engineering techniques that play an important role in analyzing and integrating large datasets. Sensor networks in particular represent a very active area of research, including work on problems such as sensor network localization and network design. Application areas for sensors and sensor networks include environmental monitoring, military surveillance, computational neuroscience, seismic detection, and a great deal more. The fundamental problems of utilizing the collected data for efficient system operation and decision making encompasses multiple research areas, including applied mathematics, optimization, signal/image processing, as well as emerging areas that require interdisciplinary techniques from several fields of research. Sensors: Theory, Algorithms, and Applications brings together recent developments from researchers representing various fields from engineering, mathematics, and computer science, along with application areas of biomedicine, transportation, and military systems. This volume is ideal for scientists, practitioners, and graduate students who are interested in the knowledge, ideas, and techniques involved in state-of-the-art sensor research.
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|a Mathematics.
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|a Algorithms.
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|a Mathematical optimization.
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|a Electronics.
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|a Microelectronics.
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|a Electrical engineering.
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|a Electronic circuits.
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|a Mathematics.
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|a Optimization.
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|a Circuits and Systems.
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|a Algorithms.
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|a Communications Engineering, Networks.
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|a Electronics and Microelectronics, Instrumentation.
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|a Boginski, Vladimir L.
|e editor.
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|a Commander, Clayton W.
|e editor.
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|a Pardalos, Panos M.
|e editor.
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|a Ye, Yinyu.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9780387886183
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|a Springer Optimization and Its Applications,
|x 1931-6828 ;
|v 61
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|u http://dx.doi.org/10.1007/978-0-387-88619-0
|z Full Text via HEAL-Link
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|a ZDB-2-SMA
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|a Mathematics and Statistics (Springer-11649)
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