Beyond the Kalman Filter: Particle Filters for Tracking Applications

by Branko Ristic, Sanjeev Arulampalam, Neil Gordon

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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... This description may be from another edition of this product.

Format:Hardcover

Language:English

ISBN:158053631X

ISBN13:9781580536318

Release Date:January 2004

Publisher:Artech House Publishers

Length:299 Pages

Weight:1.25 lbs.

Dimensions:0.9" x 6.4" x 9.3"

Related Subjects

Electrical & Electronics Engineering Technology

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Beyond the Kalman Filter: Particle Filters for Tracking Applications

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