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| Author | : Min Luo |
| Publisher | : |
| Total Pages | : 182 |
| Release | : 2001 |
| Genre | : Cupola furnaces |
| ISBN | : |
| Author | : Jitendra R. Raol |
| Publisher | : CRC Press |
| Total Pages | : 570 |
| Release | : 2009-12-16 |
| Genre | : Technology & Engineering |
| ISBN | : 1439800057 |
Using 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 | : Moises Rivas-Lopez |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 142 |
| Release | : 2017-06-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9535132539 |
Structural health monitoring (SHM) is a new engineering field with a growing tendency, based on technology development focused on data acquisition and analysis, to prevent possible damage in man-made structures and land's natural faults. The data are obtained from sensors and monitoring systems that allow detecting damages on structures, space vehicles, and land natural faults, to model their behavior under adverse scenarios, in order to search the detection of anomalies. Currently, there are many SHM systems with sensors based on different technologies like optical fiber, video cameras, optical scanners, wireless networks, and piezoelectric transducers, among others. In this context, the present book includes selected chapters with theoretical models and applications, to preserve infrastructure and prevent loss of human lives.
| Author | : Yuming Gong |
| Publisher | : Infinite Study |
| Total Pages | : 18 |
| Release | : |
| Genre | : Mathematics |
| ISBN | : |
To improve the efficiency, accuracy, and intelligence of target detection and recognition, multi-sensor information fusion technology has broad application prospects in many aspects. Compared with single sensor, multi-sensor data contains more target information and effective fusion of multi-source information can improve the accuracy of target recognition. However, the recognition capabilities of different sensors are different during target recognition, and the complementarity between sensors needs to be analyzed during information fusion. This paper proposes a multi-sensor fusion recognition method based on complementarity analysis and neutrosophic set. The proposed method mainly has two parts: complementarity analysis and data fusion. Complementarity analysis applies the trained multi-sensor to extract the features of the verification set into the sensor, and obtain the recognition result of the verification set. Based on recognition result, the multi-sensor complementarity vector is obtained. Then the sensor output the recognition probability and the complementarity vector are used to generate multiple neutrosophic sets. Next, the generated neutrosophic sets are merged within the group through the simplified neutrosophic weighted average (SNWA) operator. Finally, the neutrosophic set is converted into crisp number, and the maximum value is the recognition result. The practicality and effectiveness of the proposed method in this paper are demonstrated through examples.
| Author | : Wing Shing Wong |
| Publisher | : Chinese University Press |
| Total Pages | : 452 |
| Release | : 1995-06-22 |
| Genre | : Computers |
| ISBN | : 9789622017016 |
| Author | : Liping Yan |
| Publisher | : Springer Nature |
| Total Pages | : 229 |
| Release | : 2020-11-11 |
| Genre | : Technology & Engineering |
| ISBN | : 9811594260 |
This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.
| Author | : Xue-Bo Jin |
| Publisher | : MDPI |
| Total Pages | : 602 |
| Release | : 2020-03-23 |
| Genre | : Technology & Engineering |
| ISBN | : 3039283022 |
This 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 | : H.B. Mitchell |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 281 |
| Release | : 2007-07-13 |
| Genre | : Technology & Engineering |
| ISBN | : 3540715592 |
This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science, as well as researchers and professional engineers. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended.
| Author | : |
| Publisher | : |
| Total Pages | : 15 |
| Release | : 1996 |
| Genre | : |
| ISBN | : |
Sensor fusion research has been motivated by the difficulty of implementing automated systems which interface with the real word. For a system to react properly to a changing environment, the system requires sensor input to model its environment. Unfortunately, sensors are electromechanical devices in most cases and subject to physical limitations. There physical limitations manifest themselves as constraints on the accuracy, precision, and dependability of the data returned by the sensors. It is computationally challenging for an autonomous system to robustly evaluate sensor data of questionable accuracy and dependability. Sensor fusion seeks to solve this problem by taking inputs from several physical sensors and merging the individual physical sensor readings into a logical sensor reading. This has several advantages, some of which are particularly salient to this research effort. The use of heterogenous physical sensor allows a logical sensor to be developed which is less sensitive to the limitations of any single sensor technology.
| Author | : Abhishek Swaroop |
| Publisher | : Springer Nature |
| Total Pages | : 550 |
| Release | : 2024-01-29 |
| Genre | : Technology & Engineering |
| ISBN | : 9819965535 |
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
