Ristic branko (48 Ergebnisse)

hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Zustand: acceptable. This book is in acceptable condition and may have highlighting and or writing throughout. The actual cover image may not match the stock photo, dust jacket may be damaged or missing. Book may show internal and or external wear on spine or cover and may be slightly skewed or have creased pages. This is a used book so codes may be invalid or accompanying media may be missing. May be an Ex library book with stickers and stamps.…

Zustand: good. Signs of wear and consistent use.

Zustand: acceptable.

First Edition. Hardcover, reference copy with owner name, slight edge wear and soiling, slight spine lean.

Paperback. Zustand: New.

Zustand: New. In English.

Paperback. Zustand: New. 2013 ed. This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based  on the Monte Carlo statistical method. Although the resulting  algorithms, known as particle filters, have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.…

Zustand: As New. Unread book in perfect condition.

Zustand: New. In English.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based  on the Monte Carlo statistical method. Although the resulting  algorithms, known as particle filters, have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.…

Zustand: New.

Zustand: New.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Zustand: New. In English.

Zustand: New.

Taschenbuch. Zustand: Neu. Particle Filters for Random Set Models | Branko Ristic | Taschenbuch | xiv | Englisch | 2015 | Springer New York | EAN 9781489988843 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Hardback. Zustand: New. 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 manoeuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.…

hardcover. Zustand: New. In shrink wrap. Looks like an interesting title.

Zustand: New. InhaltsverzeichnisPart I Theoretical concepts: introduction suboptimal nonlinear filters a tutorial on particle filters Cramer-Rao bounds for nonlinear filtering. Part II Tracking applications: tracking a ballistic object bearings-on.

Paperback. Zustand: New. 2013 ed. This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based  on the Monte Carlo statistical method. Although the resulting  algorithms, known as particle filters, have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.…

Hardcover. Zustand: Brand New. 318 pages. 9.25x6.25x0.75 inches. In Stock.

Zustand: New. pp. 190.

Zustand: New. pp. 190.

Hardcover. Zustand: Brand New. 2013 edition. 188 pages. 9.00x6.25x0.50 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 299 | Sprache: Englisch | Produktart: Bücher | Filters are the basic building block of radar defense systems that track targets, provide surveillance, avoid collisions, and guide flight. The most common type of filter is the Kalman filter. For most applications the Kalman filter is reliable and efficient, but it does have limitations. This book looks at cutting-edge particle filters that can track under conditions where Kalman filters fail. It introduces the latest advances in particle filter theory, discusses their relevance to radar tracking, and examines the defense applications of particle filters. With this hands-on guide, radar engineers can develop more accurate and reliable filter designs and more precisely predict these designs' performance.…

Hardback. Zustand: New. 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 manoeuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.…