Results 21 to 30 of about 1,512,106 (277)
Localisation of mobile nodes in wireless networks with correlated in time measurement noise. [PDF]
, 2011 Wireless sensor networks are an inherent part of decision making, object tracking and location awareness systems. This work is focused on simultaneous localisation of mobile nodes based on received signal strength indicators (RSSIs) with correlated in ...
Mihaylova, Lyudmila +3 more
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A GENERIC PROBABILISTIC MODEL AND A HIERARCHICAL SOLUTION FOR SENSOR LOCALIZATION IN NOISY AND RESTRICTED CONDITIONS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 A generic probabilistic model, under fundamental Bayes’ rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors.
S. Ji, S. Ji, X. Yuan
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Wrapped Particle Filtering for Angular Data
IEEE Access, 2022 Particle filtering is probably the most widely accepted methodology for general nonlinear filtering applications. The performance of a particle filter critically depends on the choice of proposal distribution.
Guddu Kumar +4 more
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SKELETONIZATION WITH PARTICLE FILTERS [PDF]
International Journal of Pattern Recognition and Artificial Intelligence, 2010 We present a novel method to obtain high quality skeletons of binary shapes. The obtained skeletons are connected and one pixel thick. They do not require any pruning or any other post-processing. The computation is composed of two major parts. First, a small set of salient contour points is computed.
Yuchun Tang +5 more
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Nudging the particle filter [PDF]
Statistics and Computing, 2019 AbstractWe investigate a new sampling scheme aimed at improving the performance of particle filters whenever (a) there is a significant mismatch between the assumed model dynamics and the actual system, or (b) the posterior probability tends to concentrate in relatively small regions of the state space.
Ömer Deniz Akyildiz, Joaquín Míguez
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A weighted likelihood criteria for learning importance densities in particle filtering
EURASIP Journal on Advances in Signal Processing, 2018 Selecting an optimal importance density and ensuring optimal particle weights are central challenges in particle-based filtering. In this paper, we provide a two-step procedure to learn importance densities for particle-based filtering.
Muhammad Javvad ur Rehman +2 more
doaj +1 more source
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 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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