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Data Fusion for WSN Using Probabilistic Method and Particle Filter

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Bayesian Methods in the Search for MH370

distribution and validates the method using data from several of the involved aircraft's previous flights. Finally it is shown how the Reunion Island;

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Networks, Data Mining and Artificial Intelligence: Trends and Future Directions

survey on data clustering techniques. Section IV includes a probabilistic model for off-line handwritten Manipuri character recognition and a;

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Data Fusion Mathematics

be used for evaluation of the performances of any designed and developed DF systems. It tries to answer whether unified data fusion;

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Data Fusion Mathematics

be used for evaluation of the performances of any designed and developed DF systems. It tries to answer whether unified data fusion;

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Tracking with Particle Filter for High-dimensional Observation and State Spaces

This title concerns the use of a particle filter framework to track objects defined in high-dimensional state-spaces using high-dimensional;

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Biomedical Image Analysis

applications. The book next covers the major probabilistic methods for tracking. Starting with the basic Bayesian model, we describe the Kalman filter;

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Object Tracking Using Hybrid Mean Shift & Particle Filter Algorithms

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Practical Probabilistic Programming

language to build a spam filter and apply Bayesian and Markov networks to diagnose computer system data problems and recover digital images. Then;

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EMI Filter Design

plays a critical role in EMC compliance. Using a mix of practical methods and theoretical analysis, EMI Filter Design, Third Edition presents;

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EMI Filter Design

plays a critical role in EMC compliance. Using a mix of practical methods and theoretical analysis, EMI Filter Design, Third Edition presents;

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Probabilistic Forecasting and Bayesian Data Assimilation

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead;

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Probabilistic Forecasting and Bayesian Data Assimilation

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead;

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Decentralized Estimation and Control for Multisensor Systems

. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results;

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Image Fusion Techniques for Remote Sensed Data

of sensors. In order to improve the dependability for extracting information, and enhance the efficiency of the data. The image fusion results in a;

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Track-Before-Detect Using Expectation Maximisation: The Histogram Probabilistic Multi-hypothesis Tracker

chapters present applications using recorded data from experimental radar, sonar and video sensor systems. The book is supplemented with software;

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Networked Filtering and Fusion in Wireless Sensor Networks

By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make;

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Networked Filtering and Fusion in Wireless Sensor Networks

By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make;

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Surveys in Applied Mathematics

analyzes nonlinear front propagation for a large class of semi-linear partial differential equations using probabilistic methods. Particle and Wave;

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Nuclear And Particle Physics

Fusion, Radioactive Decay, Detectors, Accelerators, Reactors, and Elementary Particles. Each topic is explained with the help of simple exercises;

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Cyber-Physical System Design with Sensor Networking Technologies

cyber systems to enable efficient, secure, reliable acquisition, management, and routing of data. Topics covered include: an introduction to WSN;

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Latency and Distortion of Electromagnetic Trackers for Augmented Reality Systems

small footprint predictive filter for display lag compensation and a simplified calibration system for AC magnetic trackers. In the first;

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Wireless Sensor Networks

innovation and learning in the area of WSN. This book serves as a reference book for scientific investigators who shows an interest in evolutionary;

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Handbook of Probabilistic Models

that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil;

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Probabilistic Methods for Bioinformatics

> Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are;

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Electromagnetics and Antenna Optimization using Taguchi's Method

This book presents a new global optimization technique using Taguchi's method and its applications in electromagnetics and antenna;

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Data Fusion and Data Mining for Power System Monitoring

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining;

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