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Particle filter
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#	Item
331	Expected A Posteriori Estimation in Financial Applications Thomas Mazzoni Diskussionsbeitrag Nr. 424 April 2008 Add to Reading List Source URL: www.fernuni-hagen.de Language: English - Date: 2011-11-29 06:50:37 Estimation theory Robot control Linear filters Statistical theory Kalman filter Particle filter Unscented transform Maximum likelihood Partial differential equation Statistics Mathematics Control theory
332	WORKING PAPER NO[removed]SEQUENTIAL MONTE CARLO SAMPLING FOR DSGE MODELS Edward Herbst Federal Reserve Board Frank Schorfheide Add to Reading List Source URL: www.philadelphiafed.org Language: English - Date: 2012-11-08 13:33:02 Estimation theory Computational statistics Statistical inference Bayesian statistics Dynamic stochastic general equilibrium Particle filter Markov chain Monte Carlo Bayes estimator Identifiability Statistics Monte Carlo methods Probability and statistics
333	“Field Proven Vacuum Truck Components” Masport Inlet Filter Masport’s Inlet Filter is designed as a Add to Reading List Source URL: www.masportpump.com Language: English - Date: 2013-11-04 15:31:53 Oil filter Air filter Particle Filters Technology Chemistry
334	PhD thesis: Filter criteria for granular soils based on the Constriction Size Distribution Supervisor: E. Vincens (Ecole Centrale de Lyon) N. Reboul (Université Lyon 1) Add to Reading List Source URL: alertgeomaterials.eu Language: English - Date: 2014-06-05 09:15:12 Chemical engineering Geotechnical engineering Particle-size distribution Particulates Filtration Soil Water filter Chemistry Filters Aerosol science
335	Comparison of Kalman Filter Estimation Approaches for State Space Models with Nonlinear Measurements Fredrik Orderud Sem Sælands vei 7-9, NO-7491 Trondheim Abstract Add to Reading List Source URL: fredrik.orderud.no Language: English - Date: 2011-05-24 11:08:55 Estimation theory Signal processing Robot control Linear filters Extended Kalman filter Kalman filter Unscented transform Particle filter Nonlinear filter Statistics Electronic engineering Control theory
336	Decoding Visual Input based on V1 Neuronal Activities with Particle Filtering 1 Ryan Kelly and Tai Sing Lee Center for the Neural Basis of Cognition & Computer Science Department Carnegie Mellon University, Pittsburgh PA Add to Reading List Source URL: www.cnbc.cmu.edu Language: English - Date: 2003-08-05 10:43:56 Biology Science Nervous system Computational statistics Neural decoding Artificial neural network Neural coding Neuron Particle filter Computational neuroscience Neural networks Neuroscience
337	Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels Ryan Kelly Center for the Neural Basis of Cognition Carnegie-Mellon University Add to Reading List Source URL: www.cnbc.cmu.edu Language: English - Date: 2004-02-22 09:33:46 Nervous system Neural networks Brain Neural decoding Neural coding Particle filter Neuron Visual cortex Action potential Neuroscience Computational neuroscience Biology
338	Microsoft Word - Milford Gamma Final-dss.doc Add to Reading List Source URL: www.cemp.dri.edu Language: English - Date: 2007-10-12 16:35:34 Chemistry Nuclear physics Radiation Spectroscopy Filters Gamma spectroscopy Milford Air filter Gamma ray Physics Radioactivity Particle physics
339	Fourth Workshop on BAYESIAN INFERENCE IN STOCHASTIC PROCESSES Villa Monastero, Varenna (LC), Italy Add to Reading List Source URL: www.mi.imati.cnr.it Language: English - Date: 2005-06-02 18:40:43 Stochastic processes Statistical inference Computational statistics Hidden Markov model Mixture model Bayesian inference Dirichlet process Particle filter Gibbs sampling Statistics Markov models Bayesian statistics
340	A Tutorial on Particle Filtering and Smoothing: Fifteen years later Arnaud Doucet The Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, Tokyo[removed], Japan. Add to Reading List Source URL: www.cs.ubc.ca Language: English - Date: 2008-12-21 20:26:11 Markov models Applied mathematics Estimation theory Monte Carlo methods Linear filters Particle filter Hidden Markov model Kalman filter Importance sampling Statistics Probability and statistics Robot control

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