GitHub - AdrianGuel/StochasticProcesses: Simulation and kernel density estimation of linear and non-linear stochastic systems. Some codes include the computation of the information rate, KL-divergence and information length.

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Simulation and kernel density estimation of linear and non-linear stochastic systems. Some codes include the computation of the information rate, KL-divergence and information length.

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Name		Name	Last commit message	Last commit date
Latest commit History 23 Commits
CubicgeodesicMPC.ipynb		CubicgeodesicMPC.ipynb
CubicvsLA.ipynb		CubicvsLA.ipynb
KramersSS.m		KramersSS.m
Kramers_euler_maruyama.m		Kramers_euler_maruyama.m
Kramersequation.ipynb		Kramersequation.ipynb
Morris_Lecar_SS.ipynb		Morris_Lecar_SS.ipynb
OUEulerMaruyama.py		OUEulerMaruyama.py
OUProcessSS.m		OUProcessSS.m
OUdeterministicsimu.ipynb		OUdeterministicsimu.ipynb
OUprocess.py		OUprocess.py
Pendulumwithfriction.ipynb		Pendulumwithfriction.ipynb
citation.cff		citation.cff
cubiclaplaceassum.m		cubiclaplaceassum.m
lorentzstochastic.ipynb		lorentzstochastic.ipynb
ornstein_uhlenbeck_euler_maruyama.m		ornstein_uhlenbeck_euler_maruyama.m
ouMilstein_py.ipynb		ouMilstein_py.ipynb
stochasticsimusOU.ipynb		stochasticsimusOU.ipynb

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Simulation and kernel density estimation of linear and non-linear stochastic systems. Some codes include the computation of the information rate, KL-divergence and information length.

stochastic-processes stochastic-simulations information-length

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