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Integration of multiple adaptive algorithms for parallel decision fusion

Integration of multiple adaptive algorithms for parallel dec...

引用

Annual conference on Information Sciences and Systems (CISS)

作者： Weiqiang Dong Moshe Kam Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark New Jersey

ISBN: (纸本)9781467394581

The Chair-Varshney rule for parallel binary decision fusion requires knowledge of the a priori probabilities of the hypotheses and the performance of the sensors (probabilities of false alarm and missed detection). In most applications, this information is not available. Five methods were developed so far for estimating the unknown probabilities. However, none of them is the best under all circumstances. We present an algorithm that selects the best of these five methods. The algorithm estimates roughly the value of the a priori probabilities and the sensor performance from input data, and seeks support from a data base that provides archival data from the five methods at this operating point. In simulation, the algorithm performed on average better than each one of the five existing methods operating alone.

关键词： sensor systems Reliability sensor fusion Estimation Data integration Image sensors

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Setting governor properties on ARM architectures in image processing applications

Setting governor properties on ARM architectures in image pr...

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International conference on Emerging Technologies and Factory Automation (ETFA)

作者： Javier Silvestre-Blanes Instituto Tecnolgico de Informática (ITI) Universitat Politècnica de València (UPV) Alcoy Spain

ISBN: (纸本)9781509013159

The huge growth in the smartphones market has led to the improvement in ARM architectures, so that today there are many devices based on them, with sufficient capacity to deal with certain image processing applications. These are used in VSN (Visual sensor Networks) and in other scenarios, where the energy used in the process is a parameter to be considered. In these scenarios, and with the HMP (Heterogeneous multi-processing) architectures on which the current platforms are based, it is necessary to determine both the core as well as the working frequency in order to achieve the application's image processing objectives with the least possible energy consumption. In this type of system, the workload is oriented towards interactive applications, so the priorities are different to those of VSN type systems. Conventional regulation algorithms do not make appropriate use of the processor's frequency range, in relation to the load. This paper analyses the influence of the maximum frequency value on system performance and power consumption.

关键词： Time-frequency analysis Vehicles Smart phones Energy consumption Computer architecture Image processing Algorithm design and analysis

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Real Time Cooperative Localization for Autonomous Vehicles

Real Time Cooperative Localization for Autonomous Vehicles

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IEEE International conference on Intelligent Transportation Systems

作者： Farid Bounini Denis Gingras Herve Pollart Dominique Gruyer LIV - Université de Sherbrooke Canada OPAL-RT Technologies Inc Montreal Canada LIVIC IFSTTAR France

ISBN: (纸本)9781509018901

This paper describes a new strategy for real-time cooperative localization of autonomous vehicles. The strategy aims to improve the vehicles localization accuracy and reduce the impact of computing time of multi-sensor data fusion algorithms and vehicle-to-vehicle communication on parallel architectures. The method aims to solve localization issues in a cluster of autonomous vehicles, equipped with low-cost navigation systems in an unknown environment. It stands on multiple forms of the Kalman filter derivatives to estimate the vehicles' nonlinear model vector state, named local fusion node. The vehicles exchange their local state estimate and Covariance Intersection algorithm for merging the local vehicles' state estimate in the second node (named global data fusion node). This strategy simultaneously exploits the proprioceptive and sensors -a Global Positioning System, and a vehicle-to-vehicle transmitter and receiver - and an exteroceptive sensor, range finder, to sense their surroundings for more accurate and reliable collaborative localization.

关键词： cooperative localization Data fusion extended Kalman filter covariance intersection ADAS Transportation System autonomous vehicles V2V communication

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Reliable sources and uncertain decisions in multisensor systems

Reliable sources and uncertain decisions in multisensor syst...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Minor, Christian Johnson, Kevin Nova Res Inc Alexandria VA 22308 USA Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)9781628416145

Conflict among information sources is a feature of fused multisource and multisensor systems. Accordingly, the subject of conflict resolution has a long history in the literature of data fusion algorithms such as that of Dempster-Shafer theory (DS). Most conflict resolution strategies focus on distributing the conflict among the elements of the frame of discernment (the set of hypotheses that describe the possible decisions for which evidence is obtained) through rescaling of the evidence. These "closed-world" strategies imply that conflict is due to the uncertainty in evidence sources stemming from their reliability. An alternative approach is the "open-world" hypothesis, which allows for the presence of "unknown" elements not included in the original frame of discernment. Here, conflict must be considered as a result of uncertainty in the frame of the discernment, rather than solely the province of evidence sources. Uncertainty in the operating environment of a fused system is likely to appear as an open-world scenario. Understanding the origin of conflict (source versus frame of discernment uncertainty) is a challenging area for research in fused systems. Determining the ratio of these uncertainties provides useful insights into the operation of fused systems and confidence in their decisions for a variety of operating environments. Results and discussion for the computation of these uncertainties are presented for several combination rules with simulated data sets.

关键词： multisensor systems data fusion sensor reliability interferants open-world sensing Dempster-Shafer theory combination rules

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Data fusion Mathematics: Theory and Practice

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2015年

作者： Raol, Jiten R

ISBN: (数字)9781498721028

ISBN: (纸本)9781498721028;1498721028

Fills the Existing Gap of Mathematics for Data fusion Data fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required intelligently, using artificial intelligence (AI). Also, known as sensor data fusion (SDF), the DF fusion system is an important component for use in various applications that include the monitoring of vehicles, aerospace systems, large-scale structures, and large industrial automation plants. Data fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion, and provides a proper and adequate understanding of the basic mathematics directly related to DF. The material covered can be used for evaluation of the performances of any designed and developed DF systems. It tries to answer whether unified data fusion mathematics can evolve from various disparate mathematical concepts, and highlights mathematics that can add credibility to the data fusion process. Focuses on Mathematical Tools That Use Data fusion This text explores the use of statistical/probabilistic signal/image processing, filtering, component analysis, image algebra, decision making, and neuro-FLGA paradigms in studying, developing and validating data fusion processes (DFP). It covers major mathematical expressions, and formulae and equations as well as, where feasible, their derivations. It also discusses SDF concepts, DF models and architectures, aspects and methods of type 1 and 2 fuzzy logics, and related practical applications. In addition, the author covers soft computing paradigms that are finding increasing applications in multisensory DF approaches and applications. This book: Explores the use of interval type 2 fuzzy logic and ANFIS in DF Covers the mathematical treatment of many types of filtering algorithms, target-tracking methods, and kinematic DF methods Presents single and multi-sensor tracking and fusion mathematics Considers specific DF architectures in the context

关键词： practice theory mathematics fusion data

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Impulse noise reduction using image fusion approach

Impulse noise reduction using image fusion approach

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International conference on Innovative Computing Technology (INTECH)

作者： Najeeb Ullah Khan Sajid Ullah Khan Wang Yin Chai CECOS University Peshawar Pakistan FCSIT. Universiti Malaysia Sarawak Kuching Malaysia

ISBN: (纸本)9781509020010

Digital image enhancement has been a hot topic during the past decades. In this paper, we have established a new fusion based approach for impulse noise reduction from multi-sensors images. Image fusion is an important technique used in remote sensing, military and medical applications. In the proposed approach, firstly, only the uncorrupted pixels from multi-sensor images are grouped and then all those grouped pixels are filter with another state of the art approach for optimal results. The proposed approach is tested with several noisy images by finding the Mean Square Error, Peak Signal to Noise Ratio and Mutual Information values between the original and restored images. The experimental results show that the proposed algorithm outclasses all methods that individually de-noised and fused images.

关键词： Wiener filters Mathematical model Image restoration Optical filters Filtering algorithms Noise measurement

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An asset valuation approach using fuzzy logic

An asset valuation approach using fuzzy logic

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Leung, Henry Univ Calgary Calgary AB Canada

ISBN: (纸本)9781628416145

Organisations that own operational networks have many networked assets to support daily business. For meaningful decision support on these assets and their services, network defenders need to know the values of their assets and services. Unfortunately, there is no easy way of knowing or determining these values, and no universally recognised approach to asset valuation exists. Proprietary and published approaches, mostly in risk analysis, tend to assume values whose significance may be hard to justify in practice. Fortunately, experienced computer security experts can give intuitive guidance on the relative importance of network assets in operational networks. Such experiential knowledge, though difficult to quantify through classical relational mathematics, can be generally effective in assigning relative values to assets. In this work, we propose to capitalise on this expertise by combining asset attribute factors with expert and experiential knowledge about assets to determine their values. We exploit the mathematical theory of fuzzy logic that can be used to model and quantify human expertise and experiential knowledge. Our approach starts by modeling experts' experiential knowledge about assets and their properties as fuzzy variables. Then we use a fuzzy inference system to translate that knowledge into an asset value. Our results show asset values that are a close match with what an experienced expert would infer local asset values to be.

关键词： Alert Correlation Detection Multi-sensor

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Real Time Transducer Signal Features Extraction: A Standard Approach 13

Real Time Transducer Signal Features Extraction: A Standard ...

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13th IEEE International conference on Industrial Informatics (INDIN)

作者： Monte, G. Huang, V. Abate, F. Paciello, V. Pietrosanto, A. Univ Tecnol Nacl Fac Reg Neuquen Plaza Huincul Argentina Better World IES Stand Mishawaka IN USA Univ Salerno Dept Ind Engn I-84084 Fisciano SA Italy

ISBN: (纸本)9781479966493

This paper presents a real time algorithm, based on a segmentation and labelling technique, for analog transducer signals, which extracts information from the signal. The process of sampling is extremely important because it is the only one that connects the real world with the digital world. In addition, the proposed technique can be embedded into sensors, allowing applications in sensor networks and sensors data fusion architectures like Internet of Things. A simplified version of these algorithms has been proposed as a standard for transducer signal feature extraction. These algorithms are analysed and experimental results are tackled for representative signals, in different fields.

关键词： sampling sensor networks IoT standards real time smart sensors

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Uncertainty Characterization Using Copulas for Classification

Uncertainty Characterization Using Copulas for Classificatio...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Ozdemir, Onur Choi, Sora Allen, Thomas G. Varshney, Pramod K. Boston Fus Corp Burlington MA 01824 USA Syracuse Univ Dept EECS Syracuse NY USA

ISBN: (纸本)9781628416145

We address the problem of characterizing uncertainty for multisensor data fusion in a classification problem. To achieve this goal, we model the joint density of given multivariate data using copula functions while allowing the ability to incorporate any desired marginal distributions, i.e., any desired modalities. The proposed model is data driven in that the corresponding copula functions and their parameters are learned from the data. Our results show that the proposed framework can capture the uncertainties more accurately than current state of the practice, and lead to robust and improved classification performance compared to traditional classifiers.

关键词： Multisource data fusion copula theory classification

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Energy-efficient fuzzy logic cluster head selection in wireless sensor networks

Energy-efficient fuzzy logic cluster head selection in wirel...

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International conference on Information Technology for Organizations Development (IT4OD)

作者： Hassan El Alami Abdellah Najid STRS Lab. Institut National des Postes et Telecommunications Rabat MA STRS Lab. National Institute of Posts and Telecommunications - INPT Rabat Morocco

WSNs are characterized by limited energy constraints. This characteristic poses considerable challenge on design of routing protocols. Therefore, many designers and researchers focus on architectures and algorithms that allow energy-efficient operation of WSNs. One of the popular algorithms in this regard is clustering algorithm. Thus, there are many routing protocols based on clustering algorithm has been proposed for WSNs, the functionality of these protocols is divided into cluster heads (CHs) selection and cluster formation. However, CHs selection is one of the very important problems in routing protocols applications and can drastically impact the network lifespan thereby energy conservation task for WSNs. In this paper, we propose a new routing approach called Energy-efficient fuzzy logic cluster head (EEFL-CH); it is an improvement of LEACH protocol. The goal of this approach is to decrease energy consumption in terms of network lifetime extension using three fuzzy parameters. These parameters are residual energy, expected efficiency, and closeness to base station. Simulation results show that EEFL-CH approach has the better result as compared with LEACH and LEACH-ERE routing protocols.

关键词： Wireless sensor networks Protocols Fuzzy logic Clustering algorithms Algorithm design and analysis Steady-state Mathematical model

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