Exact Recovery of Chaotic Systems from Highly Corrupted Data
نویسندگان
چکیده
منابع مشابه
Exact Recovery of Chaotic Systems from Highly Corrupted Data
Learning the governing equations in dynamical systems from time-varying measurements is of great interest across different scientific fields. This task becomes prohibitive when such data is moreover highly corrupted, for example, due to the recording mechanism failing over unknown intervals of time. When the underlying system exhibits chaotic behavior, such as sensitivity to initial conditions,...
متن کاملShapeFit: Exact location recovery from corrupted pairwise directions
Let t1, . . . , tn ∈ R and consider the location recovery problem: given a subset of pairwise direction observations {(ti − tj)/‖ti − tj‖2}i<j∈[n]×[n], where a constant fraction of these observations are arbitrarily corrupted, find {ti}i=1 up to a global translation and scale. We propose a novel algorithm for the location recovery problem, which consists of a simple convex program over dn real ...
متن کاملData recovery from corrupted observations via l1 minimization
This paper studies the problem of recovering a signal vector and the corrupted noise vector from a collection of corrupted linear measurements through the solution of a l1 minimization (2.1.2), where the sensing matrix is a partial Fourier matrix whose rows are selected randomly and uniformly from rows of a full Fourier matrix. After choosing the parameter in (2.1.2) appropriately, we show that...
متن کاملExact Simultaneous Recovery of Locations and Structure from Known Orientations and Corrupted Point Correspondences
Let t1, . . . , tnl ∈ R and p1, . . . , pns ∈ R and consider the bipartite location recovery problem: given a subset of pairwise direction observations {(ti − pj)/‖ti − pj‖2}i,j∈[nl]×[ns], where a constant fraction of these observations are arbitrarily corrupted, find {ti}i∈[nl] and {pj}j∈[ns] up to a global translation and scale. We study the recently introduced ShapeFit algorithm as a method ...
متن کاملExact statistics of chaotic dynamical systems.
We present an inverse method to construct large classes of chaotic invariant sets together with their exact statistics. The associated dynamical systems are characterized by a probability distribution and a two-form. While our emphasis is on classical systems, we briefly speculate about possible applications to quantum field theory, in the context of generalizations of stochastic quantization.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Multiscale Modeling & Simulation
سال: 2017
ISSN: 1540-3459,1540-3467
DOI: 10.1137/16m1086637