Results 51 to 60 of about 647,012 (294)

Two Stage Particle Filter for Nonlinear Bayesian Estimation

open access: yesIEEE Access, 2018
The past several decades have witnessed the successful application of sequential Monte Carlo method (or particle filter) to a variety of fields. It has grown to be a popular method in solving different kinds of nonlinear Bayesian estimation problems ...
Fasheng Wang   +3 more
doaj   +1 more source

Joint Probabilistic Data Association-Feedback Particle Filter for Multiple Target Tracking Applications

open access: yes, 2013
This paper introduces a novel feedback-control based particle filter for the solution of the filtering problem with data association uncertainty. The particle filter is referred to as the joint probabilistic data association-feedback particle filter ...
Huang, Geng   +2 more
core   +1 more source

Identification of nonlinear lateral flow immunoassay state-space models via particle filter approach [PDF]

open access: yes, 2012
This is the post-print of the Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, the particle filtering approach is used, together with the kernel smoothing method, to identify the state ...
Du, M, Li, Y, Liu, X, Wang, Z, Zeng, N
core   +2 more sources

Multivariable feedback particle filter [PDF]

open access: yes2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
In recent work it is shown that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear filtering combined with Mean-Field Game formalisms. The resulting feedback particle filter (FPF) offers significant variance improvements; in particular, the algorithm can be applied to systems that
Yang, Tao   +3 more
openaire   +3 more sources

Monitoring of circulating tumor DNA allows early detection of disease relapse in patients with operable breast cancer

open access: yesMolecular Oncology, EarlyView.
Monitoring circulating tumor DNA (ctDNA) in patients with operable breast cancer can reveal disease relapse earlier than radiology in a subset of patients. The failure to detect ctDNA in some patients with recurrent disease suggests that ctDNA could serve as a supplement to other monitoring approaches.
Kristin Løge Aanestad   +35 more
wiley   +1 more source

Deteksi dan Pelacakan Wajah Berdasarkan Warna Kulit Menggunakan Partikel Filter

open access: yesJurnal Rekayasa Elektrika, 2018
Face detection and tracking are one of the areas which always in progress in many applications such as security system, biometric and so on. However, face detection and tracking can become a complex problem when it is done in real time condition.
Budi Sugandi
doaj   +1 more source

The Alive Particle Filter [PDF]

open access: yes, 2013
In the following article we develop a particle filter for approximating Feynman-Kac models with indicator potentials. Examples of such models include approximate Bayesian computation (ABC) posteriors associated with hidden Markov models (HMMs) or rare ...
Jasra, Ajay   +3 more
core  

LINC01116, a hypoxia‐lncRNA marker of pathological lymphangiogenesis and poor prognosis in lung adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
The LINC01116 long noncoding RNA is induced by hypoxia and associated with poor prognosis and high recurrence rates in two cohorts of lung adenocarcinoma patients. Here, we demonstrate that besides its expression in cancer cells, LINC01116 is markedly expressed in lymphatic endothelial cells of the tumor stroma in which it participates in hypoxia ...
Marine Gautier‐Isola   +12 more
wiley   +1 more source

Analisis Metode Kalman Filter, Particle Filter dan Correlation Filter Untuk Pelacakan Objek

open access: yesKomputika, 2023
Object tracking is a challenging in computer vision. Object tracking is divided into two, which can be one object or several objects, depending on the object being observed.
Ridho Sholehurrohman   +2 more
doaj   +1 more source

Consistency checks for particle filters [PDF]

open access: yes, 2006
An "inconsistent" particle filter produces - in a statistical sense - larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior.
Heijden, F. van der
core   +3 more sources

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