Multitarget-multisensor Tracking: Applications and advances
Author: Yaakov Bar-Shalom
Publisher:
Published: 1990
Total Pages: 474
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: Yaakov Bar-Shalom
Publisher:
Published: 1990
Total Pages: 474
ISBN-13:
DOWNLOAD EBOOKAuthor: Yaakov Bar-Shalom
Publisher:
Published: 1995
Total Pages: 615
ISBN-13: 9780964831209
DOWNLOAD EBOOKAuthor: Yaakov Bar-Shalom
Publisher:
Published: 1990
Total Pages: 474
ISBN-13:
DOWNLOAD EBOOKAuthor: Nikil R. Pal
Publisher: Springer Science & Business Media
Published: 2004-11-18
Total Pages: 1397
ISBN-13: 3540239316
DOWNLOAD EBOOKAnnotation This book constitutes the refereed proceedings of the 11th International Conference on Neural Information Processing, ICONIP 2004, held in Calcutta, India in November 2004. The 186 revised papers presented together with 24 invited contributions were carefully reviewed and selected from 470 submissions. The papers are organized in topical sections on computational neuroscience, complex-valued neural networks, self-organizing maps, evolutionary computation, control systems, cognitive science, adaptive intelligent systems, biometrics, brain-like computing, learning algorithms, novel neural architectures, image processing, pattern recognition, neuroinformatics, fuzzy systems, neuro-fuzzy systems, hybrid systems, feature analysis, independent component analysis, ant colony, neural network hardware, robotics, signal processing, support vector machine, time series prediction, and bioinformatics.
Author: Xue-Bo Jin
Publisher: MDPI
Published: 2020-03-23
Total Pages: 602
ISBN-13: 3039283022
DOWNLOAD EBOOKThis book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.
Author: Yunmin Zhu
Publisher: Taylor & Francis US
Published: 2003
Total Pages: 266
ISBN-13: 9781402072581
DOWNLOAD EBOOKYUNMIN ZHU In the past two decades, multi sensor or multi-source information fusion tech niques have attracted more and more attention in practice, where observations are processed in a distributed manner and decisions or estimates are made at the individual processors, and processed data (or compressed observations) are then transmitted to a fusion center where the final global decision or estimate is made. A system with multiple distributed sensors has many advantages over one with a single sensor. These include an increase in the capability, reliability, robustness and survivability of the system. Distributed decision or estimation fusion prob lems for cases with statistically independent observations or observation noises have received significant attention (see Varshney's book Distributed Detec tion and Data Fusion, New York: Springer-Verlag, 1997, Bar-Shalom's book Multitarget-Multisensor Tracking: Advanced Applications, vol. 1-3, Artech House, 1990, 1992,2000). Problems with statistically dependent observations or observation noises are more difficult and have received much less study. In practice, however, one often sees decision or estimation fusion problems with statistically dependent observations or observation noises. For instance, when several sensors are used to detect a random signal in the presence of observation noise, the sensor observations could not be statistically independent when the signal is present. This book provides a more complete treatment of the fundamentals of multi sensor decision and estimation fusion in order to deal with general random ob servations or observation noises that are correlated across the sensors.
Author: Jitendra R. Raol
Publisher: CRC Press
Published: 2009-12-16
Total Pages: 570
ISBN-13: 1439800057
DOWNLOAD EBOOKUsing MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly
Author: David Hall
Publisher: CRC Press
Published: 2001-06-20
Total Pages: 564
ISBN-13: 1420038540
DOWNLOAD EBOOKThe emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut
Author: Ronald P.S. Mahler
Publisher: Artech House
Published: 2014-08-01
Total Pages: 1167
ISBN-13: 1608077985
DOWNLOAD EBOOKThis is the sequel to the 2007 Artech House bestselling title, Statistical Multisource-Multitarget Information Fusion. That earlier book was a comprehensive resource for an in-depth understanding of finite-set statistics (FISST), a unified, systematic, and Bayesian approach to information fusion. The cardinalized probability hypothesis density (CPHD) filter, which was first systematically described in the earlier book, has since become a standard multitarget detection and tracking technique, especially in research and development. Since 2007, FISST has inspired a considerable amount of research, conducted in more than a dozen nations, and reported in nearly a thousand publications. This sequel addresses the most intriguing practical and theoretical advances in FISST, for the first time aggregating and systematizing them into a coherent, integrated, and deep-dive picture. Special emphasis is given to computationally fast exact closed-form implementation approaches. The book also includes the first complete and systematic description of RFS-based sensor/platform management and situation assessment.
Author: John Stephen Mullane
Publisher: Springer Science & Business Media
Published: 2011-05-19
Total Pages: 161
ISBN-13: 3642213898
DOWNLOAD EBOOKThe monograph written by John Mullane, Ba-Ngu Vo, Martin Adams and Ba-Tuong Vo is devoted to the field of autonomous robot systems, which have been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the problem of representing the environment and its uncertainty in terms of feature based maps. Random Finite Sets are adopted as the fundamental tool to represent a map, and a general framework is proposed for feature management, data association and state estimation. The approaches are tested in a number of experiments on both ground based and marine based facilities.