Particle Filters for Random Set Models is popular PDF and ePub book, written by Branko Ristic in 2013-04-15, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Particle Filters for Random Set Models can be Read Online from any device for your convenience.
Particle Filters for Random Set Models Book PDF Summary
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.
Detail Book of Particle Filters for Random Set Models PDF
- Author : Branko Ristic
- Release : 15 April 2013
- Publisher : Springer Science & Business Media
- ISBN : 9781461463160
- Genre : Technology & Engineering
- Total Page : 184 pages
- Language : English
- PDF File Size : 19,7 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book Particle Filters for Random Set Models by Branko Ristic, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.