Results 131 to 140 of about 780 (160)

plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors. [PDF]

Clin Cancer Res
Canzoniero JV, Rabizadeh D, Ziakas I, Wehr J, Balan A, Jamali A, Landon BV, Sivapalan L, Scott S, Pereira G, Lam VK, Hann CL, Lovly CM, Tao J, Forde PM, Murray JC, Sausen M, Meijer GA, Vink GR, Fijneman RJA, MEDOCC Group, Velculescu VE, Phallen J, Scharpf RB, Anagnostou V.   +24 more
europepmc   +1 more source

Robust Approximation of the Stochastic Koopman Operator

SIAM Journal on Applied Dynamical Systems, 2022
20 pages, six ...
Igor Mezic, Mathias Wanner
exaly   +4 more sources

On Numerical Approximations of the Koopman Operator

Mathematics, 2022
We study numerical approaches to computation of spectral properties of composition operators. We provide a characterization of Koopman Modes in Banach spaces using Generalized Laplace Analysis. We cast the Dynamic Mode Decomposition-type methods in the context of Finite Section theory of infinite dimensional operators, and provide an example of a ...
Igor Mezic, Mezic Igor
exaly   +4 more sources

Koopman Operator Spectrum for Random Dynamical Systems [PDF]

Journal of Nonlinear Science, 2019
In this paper we consider the Koopman operator associated with the discrete and the continuous time random dynamical system (RDS). We provide results that characterize the spectrum and the eigenfunctions of the stochastic Koopman operator associated with different types of linear RDS.
Nélida Črnjarić, Igor Mezic, Senka Macesic   +2 more
exaly   +5 more sources

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Sparsity Structures for Koopman and Perron--Frobenius Operators

SIAM Journal on Applied Dynamical Systems, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Schlosser, Corbinian, Korda, Milan
openaire   +2 more sources

Koopman Operator Family Spectrum for Nonautonomous Systems

SIAM Journal on Applied Dynamical Systems, 2018
For any non-autonomous dynamical system, the family of Koopman operators, as well as related Koopman eigenvalues and eigenfunctions, are parameterized by a time pair. Therefore, a logical approach in the data-driven algorithms for the non-autonomous Koopman mode decomposition is the application of a DMD method on the moving stencils of snapshots in ...
Nélida Črnjarić, Igor Mezic, Senka Macesic   +2 more
exaly   +2 more sources

Decomposition theorems for koopman operators

Nonlinear Analysis: Theory, Methods & Applications, 1997
Let \(L^1(X)= L^1_\mu(X)= L^1(X,\Sigma,\mu)\), \(L^\infty(X)= L^\infty_\mu(X)= L^\infty(X,\Sigma,\mu)\) denote the usual Lebesgue spaces on a \(\sigma\)-finite measure space \((X,\Sigma,\mu)\), and let \(S:X\to X\) be a non-singular map, i.e. \(\mu(A)=0\) implies \(\mu(S^{-1}(A))=0\), \(A\in\Sigma\). Denote \(\nu=\mu\circ S^{-1}\), \(\varphi= d\nu/d\mu\
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Koopman Operators for Estimation and Control of Dynamical Systems

Annual Review of Control, Robotics, and Autonomous Systems, 2021
A common way to represent a system's dynamics is to specify how the state evolves in time. An alternative viewpoint is to specify how functions of the state evolve in time. This evolution of functions is governed by a linear operator called the Koopman operator, whose spectral properties reveal intrinsic features of a system.
Samuel E. Otto, Clarence W. Rowley
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Koopman Operator Inspired Nonlinear System Identification

SIAM Journal on Applied Dynamical Systems, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Control based on the Koopman operator: A comprehensive review

Journal of the Franklin Institute
Luis Eduardo Garza Castanon, Luis I Minchala, Huiyan Zhang   +2 more
exaly   +2 more sources