Bokus

Branko Ristic – författare

Visar alla böcker från författaren Branko Ristic. Handla med fri frakt och snabb leverans.

4 produkter

  1. Branko Ristic - Particle Filters for Random Set Models, Inbunden. Tillgänglighet: Lägg i varukorg

    Particle Filters for Random Set Models

    Av Branko Ristic

    Inbunden, 2013

    1573 kr

    Lägg i varukorg

    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 …

  2. Branko Ristic - Particle Filters for Random Set Models, E-bok. Tillgänglighet: Lägg i varukorg

    Particle Filters for Random Set Models

    Av Branko Ristic

    E-bok, 2013

    1891 kr

    Lägg i varukorg

    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 …

  3. Branko Ristic - Particle Filters for Random Set Models, Häftad. Tillgänglighet: Lägg i varukorg

    Particle Filters for Random Set Models

    Av Branko Ristic

    Häftad, 2015

    1400 kr

    Lägg i varukorg

    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 …

  4. Branko Ristic, Sanjeev Arulampalam, Neil Gordon - Beyond the Kalman Filter, Inbunden. Tillgänglighet: Lägg i varukorg

    Beyond the Kalman Filter

    Particle Filters for Tracking Applications

    Av Branko Ristic, Sanjeev Arulampalam m. fl.

    Inbunden, 2004

    2084 kr

    Lägg i varukorg

    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 …