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Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn?
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Kalman and Bayesian Filters in Python (165个子文件)
html_build_book.bat 902B
clean_book.bat 265B
update_pdf.bat 262B
run_notebooks.bat 210B
6x9build_book.bat 187B
build_book.bat 184B
build_book6x9.bat 143B
make_chapter.bat 95B
book_to_pdf.bat 67B
build_book 209B
clean_book 450B
custom.css 5KB
2014-03-26-000-Data.csv 1.8MB
13_particle_move.gif 5.67MB
04_gaussian_animate.gif 502KB
multivariate_track1.gif 440KB
05_volt_animate.gif 430KB
02_no_info.gif 363KB
particle_filter_anim.gif 206KB
02_simulate.gif 201KB
05_dog_track.gif 197KB
multivariate_ellipse.gif 153KB
.gitattributes 94B
.gitignore 210B
license.html 911B
html_book 245B
html_build_book 1007B
08-Designing-Kalman-Filters.ipynb 3.56MB
06-Multivariate-Kalman-Filters.ipynb 2.53MB
10-Unscented-Kalman-Filter.ipynb 2.44MB
01-g-h-filter.ipynb 2.09MB
04-One-Dimensional-Kalman-Filters.ipynb 1.98MB
14-Adaptive-Filtering.ipynb 1.98MB
12-Particle-Filters.ipynb 1.92MB
05-Multivariate-Gaussians.ipynb 1.9MB
09-Nonlinear-Filtering.ipynb 1009KB
03-Gaussians.ipynb 934KB
11-Extended-Kalman-Filters.ipynb 836KB
02-Discrete-Bayes.ipynb 650KB
13-Smoothing.ipynb 517KB
1d_kf_compare.ipynb 299KB
07-Kalman-Filter-Math.ipynb 254KB
Appendix-G-Designing-Nonlinear-Kalman-Filters.ipynb 225KB
Appendix-E-Ensemble-Kalman-Filters.ipynb 220KB
1dposvel.ipynb 178KB
00-Preface.ipynb 151KB
Computing_and_plotting_PDFs.ipynb 149KB
Iterative-Least-Squares-for-Sensor-Fusion.ipynb 77KB
Interactions.ipynb 73KB
Untitled2.ipynb 63KB
Kalman_Filters_Animations.ipynb 61KB
multivariate_animations.ipynb 55KB
Appendix-D-HInfinity-Filters.ipynb 43KB
particle_animate.ipynb 35KB
discrete_bayes_animations.ipynb 28KB
Gaussians_Animations.ipynb 26KB
table_of_contents.ipynb 20KB
Appendix-A-Installation.ipynb 20KB
Converting-Multivariate-Equations-to-Univariate.ipynb 18KB
Untitled.ipynb 16KB
Taylor-Series.ipynb 14KB
Appendix-I-Analytic-Evaluation-of-Performance.ipynb 10KB
index.ipynb 6KB
Appendix-H-Least-Squares-Filters.ipynb 5KB
gating.ipynb 5KB
Appendix-B-Symbols-and-Notations.ipynb 4KB
Untitled1.ipynb 3KB
compute_q.ipynb 3KB
satellite.ipynb 2KB
Untitled0.ipynb 2KB
zarchan_ball.ipynb 1KB
538.json 783B
README.md 19KB
gh_estimate3.png 34KB
residual_chart_with_h.png 31KB
gh_estimate2.png 31KB
residual_chart.png 30KB
gh_hypothesis1.png 26KB
gh_estimate1.png 24KB
gh_hypothesis5.png 21KB
gh_hypothesis4.png 19KB
gh_predict_update.png 17KB
gh_hypothesis3.png 16KB
gh_hypothesis2.png 15KB
gh_errorbar1.png 6KB
gh_errorbar2.png 6KB
gh_errorbar3.png 6KB
book_plots.py 15KB
mkf_internal.py 14KB
ukf_internal.py 13KB
pf_internal.py 12KB
nonlinear_plots.py 9KB
RobotLocalizationParticleFilter.py 9KB
ball.py 8KB
gh_internal.py 8KB
ekf_internal.py 7KB
ekfloc3.py 6KB
ekfloc.py 6KB
RobotLocalizationParticleFilter_2.py 6KB
two_radar.py 6KB
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