Sampled-data control under time-varying delays: a robust approach for high-renewable smart grids. [PDF]
Sci RepHassan M.
europepmc +1 more source
Uncertainty Quantification of Finite Element Strain Predictions for a Nitinol Medical Device: Influence of Input Parameter Probability Distribution on Output Uncertainty. [PDF]
Cardiovasc Eng TechnolCarr IA +5 more
europepmc +1 more source
Configuration identification of on-demand variable stiffness strain-limiting layers in zig-zag soft pneumatic actuators using deep learning methods. [PDF]
Int J Rob ResGunawardane PDSH +5 more
europepmc +1 more source
A Novel Particle Filter Based on One-Step Smoothing for Nonlinear Systems with Random One-Step Delay and Missing Measurements. [PDF]
Sensors (Basel)Yang Z, Zhang X, Xiang W, Lin X.
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The Labeled Multi-Bernoulli Filter
IEEE Transactions on Signal Processing, 2014 This paper proposes a generalization of the multi- Bernoulli filter called the labeled multi-Bernoulli filter that outputs target tracks. Moreover, the labeled multi-Bernoulli filter does not exhibit a cardinality bias due to a more accurate update approximation compared to the multi-Bernoulli filter by exploiting the conjugate prior form for labeled ...
Ba-Ngu Võ +2 more
exaly +4 more sources
Multi-Scan Generalized Labeled Multi-Bernoulli Filter
2018 21st International Conference on Information Fusion (FUSION), 2018 This paper extends the generalized labeled multi-Bernoulli (GLMB) tracking filter to a batch multi-target tracker. In a labeled random finite set formulation, a multi-target tracking filter propagates the labeled multi-target filtering density while a batch multi-target tracker propagates the labeled multi-target posterior density.
Ba-Tuong Vo, Ba-Ngu Vo
openaire +2 more sources
A Fast Labeled Multi-Bernoulli Filter Using Belief Propagation
IEEE Transactions on Aerospace and Electronic Systems, 2020 We propose a fast labeled multi-Bernoulli (LMB) filter that uses belief propagation for probabilistic data association. The complexity of our filter scales only linearly in the numbers of Bernoulli components and measurements, while the Performance is ...
Thomas Kropfreiter +2 more
exaly +2 more sources
Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2018 We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multitarget tracking with the standard point target measurements without using probability generating functionals or functional derivatives. We also establish the connection
Angel F García-Fernández +2 more
exaly +2 more sources