[PDF] Divergent Tracks eBook

Author : Vanessa Theme Ament
Publisher : Bloomsbury Publishing USA
Page : 176 pages
File Size : 32,67 MB
Release : 2021-04-22
Category : Performing Arts
ISBN : 1501359207

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By examining three case studies of award-winning soundtracks from cult films-Barton Fink (1991), Bram Stoker's Dracula (1992), and The English Patient (1996)-it becomes clear that major American film communities, when confronted with the initial technological changes of the 1990s, experienced similar challenges with the inelegant transition from analogue to digital. However, their cultural and structural labor differences governed different results. Vanessa Ament, author of The Foley Grail (2009), rather than defining the 1990s as an era of technological determinism-a superficial reading-it is best understood as one in which sound professionals became more viable as artists, collaborated in sound design authorship, and influenced this digital transition to better accommodate their needs and desires in their work.

Author : Robert L. Fleischer
Publisher : Springer Science & Business Media
Page : 218 pages
File Size : 21,2 MB
Release : 1998-01-12
Category : Science
ISBN : 9780387983424

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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 : Branko Ristic
Publisher : Artech House
Page : 328 pages
File Size : 43,42 MB
Release : 2003-12-01
Category : Technology & Engineering
ISBN : 9781580538510

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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 : Anton J. Haug
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 22,68 MB
Release : 2012-05-29
Category : Mathematics
ISBN : 1118287800

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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.