5 Papers
62 Citations
J. Ye is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Hamiltonian system & Hamiltonian (control theory). The author has an hindex of 4, co-authored 5 publications.
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Papers
Systematic variational method for statistical nonlinear state and parameter estimation.
J. Ye,Daniel Rey,Nirag Kadakia,Michael Eldridge,Uriel I. Morone,Paul J. Rozdeba,Henry D. I. Abarbanel,John C. Quinn +7 more
TL;DR: In this article, an annealing method for locating the variational path satisfying the Euler-Lagrange equations that comprises the major contribution to the integrals is presented.
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Estimating the biophysical properties of neurons with intracellular calcium dynamics.
TL;DR: It is shown that observing both the voltage time course V(t) and the intracellular Ca time course will permit accurate estimation, and from the estimated model state, accurate prediction after observations are completed, setting the stage for how one will be able to use a more detailed model of V+Ca dynamics in neuron activity in the analysis of experimental data on individual neurons as well as functional networks in which the nodes have these biophysical properties.
18
Symplectic structure of statistical variational data assimilation
TL;DR: In this paper, the authors explore the implications of this structure in both Lagrangian coordinates {x(t),x (t)} and Hamiltonian canonical coordinates { x(t,p(t)} through a numerical examination of the chaotic Lorenz 1996 model in ten dimensions.
10
Precision variational approximations in statistical data assimilation
J. Ye,N. Kadakia,Paul J. Rozdeba,H. D. I. Abarbanel,John C. Quinn +4 more
- 01 Oct 2014
Abstract: Introduction Conclusions References Tables Figures
Improved variational methods in statistical data assimilation
TL;DR: In this article, a path integral formulation of statistical data assimilation is considered in a realization of the action where measurement errors and model errors are Gaussian, and an annealing method for locating the path X0 giving a consistent minimum of the "action" A0(X0) is discussed.