Particle Gaussian mixture filters-I
Copyright policy )Particle Gaussian mixture filters-I
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
- The University of Texas System United States
- Texas A&M University United States
Estimation and detection in stochastic control theory, Software, source code, etc. for problems pertaining to systems and control theory, parallel algorithms, estimation algorithms, Markov chain Monte Carlo sampling, curse of dimensionality, Filtering in stochastic control theory, nonlinear filters, machine learning, particle filtering, Gaussian mixture models, state estimation, Kalman filters, multimodality
Estimation and detection in stochastic control theory, Software, source code, etc. for problems pertaining to systems and control theory, parallel algorithms, estimation algorithms, Markov chain Monte Carlo sampling, curse of dimensionality, Filtering in stochastic control theory, nonlinear filters, machine learning, particle filtering, Gaussian mixture models, state estimation, Kalman filters, multimodality
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).49 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
Citations provided by BIP!Popularity provided by BIP!