Transcription of BAYESIAN FILTERING AND SMOOTHING - Aalto
{{id}} {{{paragraph}}}
This PDF version is made available for personal use. The copyright in all material rests with the author (Simo S arkk a). Commercialreproduction is prohibited, except as authorised by the author and FILTERING ANDSMOOTHINGSimo S arkk aBayesian FILTERING and Smoothinghas beenpublished by Cambridge University Press, asvolume 3 in the IMS Textbooks series. It can bepurchased directly from Cambridge cite this book as:Simo S arkk a (2013). BAYESIAN FILTERING andSmoothing. Cambridge University PDF version is made available for personal use. The copyright in all material rests with the author (Simo S arkk a). Commercialreproduction is prohibited, except as authorised by the author and PDF version is made available for personal use. The copyright in all material rests with the author (Simo S arkk a).
Stratonovich in the 1950s and 1960s – even before Kalman’s seminal arti-cle in 1960. Thus the theory of non-linear filtering has been Bayesian from the beginning (see Jazwinski, 1970). Chapter 1 is a general introduction to the idea and applications of Bayesian filtering and smoothing. The purpose of Chapter 2 is to briefly
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
{{id}} {{{paragraph}}}