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GitHub / baggepinnen / LowLevelParticleFilters.jl
State estimation, smoothing and parameter estimation using Kalman and particle filters.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/baggepinnen%2FLowLevelParticleFilters.jl
Stars: 112
Forks: 15
Open Issues: 6
License: other
Language: Julia
Repo Size: 191 MB
Dependencies:
8
Created: over 6 years ago
Updated: 4 days ago
Last pushed: 4 days ago
Last synced: 4 days ago
Commit Stats
Commits: 344
Authors: 11
Mean commits per author: 31.27
Development Distribution Score: 0.462
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/baggepinnen/LowLevelParticleFilters.jl
Topics: bayesian-inference, control-systems, controls, data-assimilation, dynamical-systems, estimation, extended-kalman-filter, kalman-filter, monte-carlo-methods, parameter-estimation, particle-filter, prediction-error-method, sequential-monte-carlo, state-estimation, state-estimation-algorithms, state-estimation-filters, system-identification, unscented-kalman-filter, virtual-sensing, virtual-sensors
Files
Dependencies
- JuliaRegistries/TagBot v1 composite
- actions/checkout v2 composite
- julia-actions/setup-julia latest composite
- actions/checkout v2 composite
- codecov/codecov-action v1 composite
- julia-actions/julia-processcoverage v1 composite
- julia-actions/julia-runtest latest composite
- julia-actions/setup-julia latest composite