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Particle filter
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#	Item
201	MECHANISMS OF FILTRATION FOR HIGH EFFICIENCY FIBROUS FILTERS APPLICATION NOTE ITI-041 (A4) Overview Add to Reading List Source URL: www.tsi.com Language: English - Date: 2012-08-29 16:38:23 Technology HEPA Respirator Cleanroom Air filter Filtration Brownian motion Particle Molecular diffusion Filters Chemistry Chemical engineering
202	Department of Automatic Control & Systems Engineering would like to announce the following seminar: Localisation in Wireless Networks Using Monte Carlo Methods Speaker: Dr Mila Mihaylova Add to Reading List Source URL: www.sheffield.ac.uk Language: English - Date: 2011-07-19 20:20:18 Statistics Particle filter Monte Carlo method Wireless sensor network Received signal strength indication Wireless network Wireless ad-hoc network Estimation theory Localization Wireless networking Technology Wireless
203	Mobility Tracking in Cellular Networks with Sequential Monte Carlo Filters Lyudmila Mihaylova∗ , David Bull∗ , Donka Angelova∗∗ and Nishan Canagarajah∗ ∗ Department of Electrical and Electronic Engineering, U Add to Reading List Source URL: eprints.lancs.ac.uk Language: English - Date: 2011-01-27 19:54:54 Control theory Estimation theory Electronic engineering Signal processing Linear filters Kalman filter Particle filter Vehicle Identification Number Markov chain Statistics Robot control Markov models
204	Appl Phys B[removed]: 403–409 DOI[removed]s00340[removed]Linear optimal control for tracking a single fluorescent particle in a confocal microscope S.B. Andersson · T. Sun Add to Reading List Source URL: people.bu.edu Language: English - Date: 2009-02-04 20:36:10 Robot control Linear filters Electronic engineering Control theory Kalman filter Gaussian function Estimation theory Fluorescence correlation spectroscopy Science Signal processing Statistics
205	Particle Filtering with Factorized Likelihoods for Tracking Facial Features I. Patras and M. Pantic Knowledge and Data Engineering Group Delft University of Technology Mekelweg 4, 2628 CD Delft The Netherlands Add to Reading List Source URL: ibug.doc.ic.ac.uk Language: English - Date: 2010-11-25 10:09:18 Physics Matter Statistics Particle filter Robot control Leptons Particle Auxiliary particle filter Neutrino Monte Carlo methods Computational statistics Estimation theory
206	Research Screening Committee Meeting Advance Agenda January 30, 2015 Add to Reading List Source URL: www.arb.ca.gov Language: English - Date: 2015-01-15 14:55:34 Particulates Smog Environment of California Black carbon Ultrafine particle Portable emissions measurement system Diesel exhaust Diesel particulate filter Not-To-Exceed Pollution Air pollution Atmosphere
207	Building Hybrid Rover Models: Lessons Learned Thomas Willeke1 and Richard Dearden2 Abstract. Particle filters have recently become popular for diagnosis and monitoring of hybrid systems. In this paper we describe our exp Add to Reading List Source URL: www.sunspiral.org Language: English - Date: 2008-05-10 23:44:34 Robot control Estimation theory Computational statistics Markov models Linear filters Particle filter Kalman filter Rover Company Diagnosis Robotics Statistics Spaceflight
208	Real-time Fault Detection and Situational Awareness for Rovers: Report on the Mars Technology Program Task Richard Dearden, Thomas Willeke {RIACS, QSS Group Inc.} / NASA Ames Research Center M.S[removed], Moffett Field, CA Add to Reading List Source URL: www.sunspiral.org Language: English - Date: 2008-05-10 23:44:33 Control theory Electronic engineering Markov models Monte Carlo methods Linear filters Particle filter Extended Kalman filter Kalman filter Normal distribution Statistics Robot control Estimation theory
209	ASSIMILATING GLOBALBEDO DATA INTO THE JULES LAND SURFACE MODEL Tristan Quaife ECMWF 17th September 2014 Add to Reading List Source URL: www.ecmwf.int Language: English - Date: 2014-09-24 08:23:34 Control theory Bayesian statistics Robot control Data assimilation Particle filter Resampling Ensemble Kalman filter Kalman filter Inverse problem Statistics Monte Carlo methods Estimation theory
210	Séminaire Lundi 3 fevrier[removed]:00h / Seminar Monday February 3rd[removed]:00h Sujet/Subject: Clever particle filters, sequential importance sampling and the optimal proposal . Conférencier/Lecturer: Chris Snyder, (NC Add to Reading List Source URL: collaboration.cmc.ec.gc.ca Language: English - Date: 2014-01-29 11:45:08 Estimation theory Particle filter Robot control Electronic engineering Importance sampling Signal processing Filter Electronic filter Monte Carlo methods Statistics Computational statistics

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