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Author: Anton J. Haug
Publisher: John Wiley & Sons
ISBN: 1118287800
Category : Mathematics
Languages : en
Pages : 400
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Book Description
A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for Gaussian-weighted integrals and particle filters for non-Gaussian cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand. Case studies are employed to showcase applications of the discussed topics. In addition, the book supplies block diagrams for each algorithm, allowing readers to develop their own MATLAB® toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book for courses on estimation and tracking methods at the graduate level. The book also serves as a valuable reference for research scientists, mathematicians, and engineers seeking a deeper understanding of the topics.
Author: Anton J. Haug
Publisher: John Wiley & Sons
ISBN: 1118287800
Category : Mathematics
Languages : en
Pages : 400
Get Book Here
Book Description
A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for Gaussian-weighted integrals and particle filters for non-Gaussian cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand. Case studies are employed to showcase applications of the discussed topics. In addition, the book supplies block diagrams for each algorithm, allowing readers to develop their own MATLAB® toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book for courses on estimation and tracking methods at the graduate level. The book also serves as a valuable reference for research scientists, mathematicians, and engineers seeking a deeper understanding of the topics.
Author: Robert L. Fleischer
Publisher: Springer Science & Business Media
ISBN: 1461244528
Category : Science
Languages : en
Pages : 199
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Book Description
In the late 1950s, scientists at General Electric -- among them the author -- discovered that when mica is exposed to energetic charged particles, the particles leave latent tracks in the material. It soon turned out that glass, plastics, or certain other materials can be similarly treated. This discovery paved the way not only for a new and useful method of measuring radioactivity, it has also found widespread applications in other fields, ranging from geology and materials science to archaeology and art history. Fleischer presents the history of these developments and discusses the applications of the technique in a way that will interest anyone even with only a minimal knowledge of physics.
Author: United States. Patent Office
Publisher:
ISBN:
Category : Patents
Languages : en
Pages : 816
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Book Description
Author:
Publisher:
ISBN:
Category : Patents
Languages : en
Pages : 1676
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Book Description
Author: Samuel J. Davey
Publisher: Springer
ISBN: 981107593X
Category : Technology & Engineering
Languages : en
Pages : 357
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Book Description
This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on the method. Beginning with basic concepts, the authors then move on to address extensions of the method to a broad class of tracking problems. The latter chapters present applications using recorded data from experimental radar, sonar and video sensor systems.
Author: Charles Mears Kurtz
Publisher:
ISBN:
Category : Railroad engineering
Languages : en
Pages : 482
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 910
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Book Description
Author: Wise Publications
Publisher: Wise Publications
ISBN: 1783235470
Category : Music
Languages : en
Pages : 47
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Book Description
Really Easy Piano: Songs From The Movies is packed with 16 songs from your favourite films, all arranged for easy Piano Featuring the best songs from the biggest Hollywood blockbusters in recent years, this collection will allow you to recreate the magic of the movies in your own bedroom from 'Frozen' to ‘Skyfall’ to ‘The Hunger Games’ Each piece features an insight into the song itself, as well as some really useful playing hints and tips to ensure you master each and every score. So, if you're a fan of the biggest movie soundtracks, or you are just a fanatical film buff, this Really Easy Piano: Songs From The Movies collection will quench your thirst for those uplifting songs that make us fall in love with cinema.M Songlist: - Atlas (The Hunger Games: Catching Fire) - Beating Heart (Divergent) - Boom Clap (The Fault In Our Stars) - Eyes Open (The Hunger Games) - Everything Is Awesome!!! (Tegan & Sara) - Girls Just Want To Have Fun (Walking On Sunshine) - Happy (Despicable Me 2) - Hooked On A Feelin' (Guardians Of The Galaxy) - Man Or Muppet (The Muppets) - I See Fire (The Hobbit: The Desolation Of Smaug) - Let It Go (Frozen) - Once Upon A Dream (Maleficent) - Over The Love (The Great Gatsby) - Skyfall (Skyfall) - Suddenly (Les Misérables) - A Thousand Years (Twilight: Breaking Dawn Part 1)
Author: Branko Ristic
Publisher: Artech House
ISBN: 9781580538510
Category : Technology & Engineering
Languages : en
Pages : 328
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Book Description
For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. Packed with 867 equations, this cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems. With this hands-on guide, you can develop more accurate and reliable nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of maneuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.
Author: J. Michael Martinez
Publisher: CRC Press
ISBN: 0415633184
Category : Law
Languages : en
Pages : 1227
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Book Description
Protecting the natural environment and promoting sustainability have become important objectives, but achieving such goals presents myriad challenges for even the most committed environmentalist. American Environmentalism: Philosophy, History, and Public Policy examines whether competing interests can be reconciled while developing consistent, coherent, effective public policy to regulate uses and protection of the natural environment without destroying the national economy. It then reviews a range of possible solutions. The book delves into key normative concepts that undergird American perspectives on nature by providing an overview of philosophical concepts found in the western intellectual tradition, the presuppositions inherent in neoclassical economics, and anthropocentric (human-centered) and biocentric (earth-centered) positions on sustainability. It traces the evolution of attitudes about nature from the time of the Ancient Greeks through Europeans in the Middle Ages and the Renaissance, the Enlightenment and the American Founders, the nineteenth and twentieth centuries, and up to the present. Building on this foundation, the author examines the political landscape as non-governmental organizations (NGOs), industry leaders, and government officials struggle to balance industrial development with environmental concerns. Outrageous claims, silly misrepresentations, bogus arguments, absurd contentions, and overblown prophesies of impending calamities are bandied about by many parties on all sides of the debate—industry spokespeople, elected representatives, unelected regulators, concerned citizens, and environmental NGOs alike. In lieu of descending into this morass, the author circumvents the silliness to explore the crucial issues through a more focused, disciplined approach. Rather than engage in acrimonious debate over minutiae, as so often occurs in the context of "green" claims, he recasts the issue in a way that provides a cohesive look at all sides. This effort may be quixotic, but how else to cut the Gordian knot?
