Sensors: Theory, Algorithms, and Applications
Title: Sensors: Theory, Algorithms, and Applications
Authors: Vladimir L. Boginski, Clayton W. Commander, Panos M. Pardalos, Yinyu Ye
Hardcover: 252 pages
The objective of this book is to advance the current knowledge of sensor research particularly highlighting recent advances, current work, and future needs. The goal is to share current technologies and steer future efforts in directions that will benefit the majority of researchers and practitioners working in this broad field of study.
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.
Part I. Models and Algorithms for Ensuring Efficient
Performance of Sensor Networks on Enhancing Fault Tolerance of Virtual Backbone in a Wireless Sensor Network with Unidirectional Links . . .3
Ravi Tiwari and My T. Thai
Constrained Node Placement and Assignment in Mobile Backbone Networks . . . 19
Emily M. Craparo
Canonical Dual Solutions to Sum of Fourth-Order Polynomials Minimization Problems with Applications to Sensor Network Localization . . . 37
David Yang Gao, Ning Ruan, and Panos M. Pardalos
Part II. Theoretical Aspects of Analyzing Information Patterns
Optimal Estimation of Multidimensional Data with Limited Measurements . . . 57
William MacKunis, J. Willard Curtis, and Pia E.K. Berg-Yuen
Information Patterns in Discrete-Time Linear-Quadratic Dynamic Games . . . 83
Meir Pachter and Khanh D. Pham
The Design of Dynamical Inquiring Systems: A Certainty Equivalent Formalization . . . 119
Laura Di Giacomo and Giacomo Patrizi
Part III. Sensors in Real-World Applications
Sensors in Transportation and Logistics Networks. . .145
Study of Mobile Mixed Sensing Networks in an Automotive Context. . . . . 165
Animesh Chakravarthy, Kyungyeol Song, Jaime Peraire, and Eric Feron
Navigation in Difficult Environments: Multi-Sensor Fusion Techniques . . .199
Andrey Soloviev and Mikel M. Miller'
A Spectral Clustering Approach for Modeling Connectivity Patterns in Electroencephalogram Sensor Networks. . .231
Petros Xanthopoulos, Ashwin Arulselvan, and Panos M. Pardalos
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