Results 31 to 40 of about 61,960 (301)
Particle filtering with alpha-stable distributions [PDF]
, 2005 In this paper we introduce a novel sequential Monte Carlo technique, which is based on the family of symmetric alpha- stable (SAS) distributions.
D. Bull +9 more
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Covariance Tracking via Geometric Particle Filtering
EURASIP Journal on Advances in Signal Processing, 2010 Region covariance descriptor recently proposed has been approved robust and elegant to describe a region of interest, which has been applied to visual tracking.
Yunpeng Liu, Guangwei Li, Zelin Shi
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A rank correlation coefficient based particle filter to estimate parameters in non-linear models
International Journal of Distributed Sensor Networks, 2019 Particle filtering algorithm has found an increasingly wide utilization in many fields at present, especially in non-linear and non-Gaussian situations. Because of the particle degeneracy limitation, various resampling methods have been researched.
Qingxu Meng, Kaicheng Li
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An Improved Particle Filtering Algorithm and Its Application in Multipath Estimation [PDF]
Jisuanji gongcheng, 2017 Aiming at the problem of particle depletion in traditional Particle Filtering(PF),a PF algorithm based on Adaptive Differential Evolution(ADE) is proposed.The ADE algorithm instead of the re-sampling strategy is used to generate new particles in PF,which
WANG Zhiyuan,CHENG Lan,XIE Gang
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Tempered Particle Filtering [PDF]
Finance and Economics Discussion Series, 2016 The accuracy of particle filters for nonlinear state-space models crucially depends on the proposal distribution that mutates time t-1 particle values into time t values. In the widely-used bootstrap particle filter this distribution is generated by the state-transition equation.
Edward Herbst, Frank Schorfheide
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A Probabilistic Perspective on Gaussian Filtering and Smoothing [PDF]
, 2010 15.07.13 KB. Ok to add report to Spiral.We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of ...
Deisenroth, MP, Ohlsson, H
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Probability hypothesis density filtering for real-time traffic state estimation and prediction [PDF]
, 2013 The probability hypothesis density (PHD) methodology is widely used by the research community for the purposes of multiple object tracking. This problem consists in the recursive state estimation of several targets by using the information coming from an
El Faouzi, Nour Eddin +9 more
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Linear and nonlinear filtering in mathematical finance: a review [PDF]
, 2010 Copyright @ The Authors 2010This paper presents a review of time series filtering and its applications in mathematical finance. A summary of results of recent empirical studies with market data are presented for yield curve modelling and stochastic ...
Date, P +3 more
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An improved unbiased particle filter
Monte Carlo Methods and Applications, 2023 Abstract In this paper, we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical reasons, one has to time-discretize the diffusion process, which typically leads to filtering that is subject to discretization bias. The approach in [A.
Ajay Jasra +2 more
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