Delay-Coordinate Maps and the Spectra of Koopman Operators
暂无分享,去创建一个
[1] T. Sauer,et al. Local Kernels and the Geometric Structure of Data , 2014, 1407.1426.
[2] W. Petryshyn. On the eigenvalue problem Tu-λSu=0 with unbounded and nonsymetric operators T and S , 1968, Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences.
[3] Dimitrios Giannakis,et al. Extraction and prediction of coherent patterns in incompressible flows through space–time Koopman analysis , 2017, 1706.06450.
[4] Mikhail Belkin,et al. Convergence of Laplacian Eigenmaps , 2006, NIPS.
[5] T. Eisner,et al. Ergodic Theorems , 2019, Probability.
[6] Lai-Sang Young,et al. What Are SRB Measures, and Which Dynamical Systems Have Them? , 2002 .
[7] Mark J. McGuinness,et al. The fractal dimension of the Lorenz attractor , 1983 .
[8] Dejan Slepcev,et al. A variational approach to the consistency of spectral clustering , 2015, Applied and Computational Harmonic Analysis.
[9] V. A. Menegatto,et al. Eigenvalues of Integral Operators Defined by Smooth Positive Definite Kernels , 2009 .
[10] Victor Montagud-Camps. Turbulence , 2019, Turbulent Heating and Anisotropy in the Solar Wind.
[11] D. Giannakis,et al. Nonparametric forecasting of low-dimensional dynamical systems. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[12] P. Holmes,et al. Turbulence, Coherent Structures, Dynamical Systems and Symmetry: THE BOUNDARY LAYER , 1996, The Aeronautical Journal (1968).
[13] Steven L. Brunton,et al. Chaos as an intermittently forced linear system , 2016, Nature Communications.
[14] T. Eisner,et al. Operator Theoretic Aspects of Ergodic Theory , 2015 .
[15] D. Giannakis. Data-driven spectral decomposition and forecasting of ergodic dynamical systems , 2015, Applied and Computational Harmonic Analysis.
[16] P. Schmid,et al. Dynamic mode decomposition of numerical and experimental data , 2008, Journal of Fluid Mechanics.
[17] M. Stone. On One-Parameter Unitary Groups in Hilbert Space , 1932 .
[18] V. A. Menegatto,et al. Eigenvalue decay rates for positive integral operators , 2013 .
[19] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[20] Igor Mezic,et al. On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator , 2017, J. Nonlinear Sci..
[21] P. Holmes,et al. Turbulence, Coherent Structures, Dynamical Systems and Symmetry , 1996 .
[22] Stéphane Lafon,et al. Diffusion maps , 2006 .
[23] R. Téman,et al. Integral Manifolds and Inertial Manifolds for Dissipative Partial Differential Equations , 1988 .
[24] Dimitrios Giannakis,et al. Dynamics-Adapted Cone Kernels , 2014, SIAM J. Appl. Dyn. Syst..
[25] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[26] Steven L. Brunton,et al. On dynamic mode decomposition: Theory and applications , 2013, 1312.0041.
[27] Alain Largillier,et al. Spectral Computations for Bounded Operators , 2001 .
[28] Mikhail Belkin,et al. Consistency of spectral clustering , 2008, 0804.0678.
[29] Morten Hjorth-Jensen. Eigenvalue Problems , 2021, Explorations in Numerical Analysis.
[30] Michael Dellnitz,et al. On the isolated spectrum of the Perron-Frobenius operator , 2000 .
[31] Andrzej Banaszuk,et al. Comparison of systems with complex behavior , 2004 .
[32] B. O. Koopman,et al. Hamiltonian Systems and Transformation in Hilbert Space. , 1931, Proceedings of the National Academy of Sciences of the United States of America.
[33] Ian Melbourne,et al. The Lorenz Attractor is Mixing , 2005 .
[34] E. Lorenz. Deterministic nonperiodic flow , 1963 .
[35] Milan Korda,et al. Data-driven spectral analysis of the Koopman operator , 2017, Applied and Computational Harmonic Analysis.
[36] Zhizhen Zhao,et al. Spatiotemporal Feature Extraction with Data-Driven Koopman Operators , 2015, FE@NIPS.
[37] Andrew J. Majda,et al. Time Series Reconstruction via Machine Learning: Revealing Decadal Variability and Intermittency in the North Pacific Sector of a Coupled Climate Model. , 2011, CIDU 2011.
[38] Tyrus Berry,et al. Consistent manifold representation for topological data analysis , 2016, Foundations of Data Science.
[39] W. Tucker. The Lorenz attractor exists , 1999 .
[40] C. Caramanis. What is ergodic theory , 1963 .
[41] P. Halmos. Lectures on ergodic theory , 1956 .
[42] A. Majda,et al. Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability , 2012, Proceedings of the National Academy of Sciences.
[43] R. Vautard,et al. Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series , 1989 .
[44] D. Giannakis,et al. Koopman spectra in reproducing kernel Hilbert spaces , 2018, 1801.07799.
[45] G. P. King,et al. Extracting qualitative dynamics from experimental data , 1986 .
[46] Timothy D. Sauer,et al. Time-Scale Separation from Diffusion-Mapped Delay Coordinates , 2013, SIAM J. Appl. Dyn. Syst..
[47] O. Junge,et al. On the Approximation of Complicated Dynamical Behavior , 1999 .
[48] Kevin Barraclough,et al. I and i , 2001, BMJ : British Medical Journal.
[49] J. Harlim,et al. Variable Bandwidth Diffusion Kernels , 2014, 1406.5064.
[50] B. Fayad. Analytic mixing reparametrizations of irrational flows , 2002, Ergodic Theory and Dynamical Systems.
[51] Clarence W. Rowley,et al. A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition , 2014, Journal of Nonlinear Science.
[52] P. Constantin,et al. Diffusion and mixing in fluid flow , 2005 .
[53] I. Mezić,et al. Applied Koopmanism. , 2012, Chaos.
[54] G. Froyland,et al. Almost-invariant sets and invariant manifolds — Connecting probabilistic and geometric descriptions of coherent structures in flows , 2009 .
[55] Igor Mezic,et al. Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator , 2016, SIAM J. Appl. Dyn. Syst..
[56] James P. Crutchfield,et al. Geometry from a Time Series , 1980 .
[57] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[58] Evarist Giné,et al. Empirical Processes , 2011, International Encyclopedia of Statistical Science.
[59] I. Mezić. Spectral Properties of Dynamical Systems, Model Reduction and Decompositions , 2005 .
[60] Clara Deser,et al. El Niño and Southern Oscillation (ENSO): A Review , 2017 .
[61] Zeng Lian,et al. SRB Measures for A Class of Partially Hyperbolic Attractors in Hilbert spaces , 2015, 1508.03301.
[62] Nadine Aubry,et al. Spatiotemporal analysis of complex signals: Theory and applications , 1991 .
[63] Marc G. Genton,et al. Classes of Kernels for Machine Learning: A Statistics Perspective , 2002, J. Mach. Learn. Res..
[64] I. Mezić,et al. Spectral analysis of nonlinear flows , 2009, Journal of Fluid Mechanics.
[65] Ronald R. Coifman,et al. Graph Laplacian Tomography From Unknown Random Projections , 2008, IEEE Transactions on Image Processing.
[66] Lai-Sang Young,et al. Strange Attractors for Periodically Forced Parabolic Equations , 2013 .
[67] Pietro Perona,et al. Self-Tuning Spectral Clustering , 2004, NIPS.
[68] Gary Froyland,et al. A Computational Method to Extract Macroscopic Variables and Their Dynamics in Multiscale Systems , 2013, SIAM J. Appl. Dyn. Syst..
[69] Dimitrios Giannakis,et al. Indo-Pacific variability on seasonal to multidecadal timescales. Part I: Intrinsic SST modes in models and observations , 2016, 1604.01742.
[70] Gary Froyland,et al. Detecting isolated spectrum of transfer and Koopman operators with Fourier analytic tools , 2014 .
[71] Jihui Zhang,et al. Infinitely many small solutions for the p(x)-Laplacian operator with nonlinear boundary conditions , 2013 .
[72] A. Stuart,et al. Analysis of the 3DVAR filter for the partially observed Lorenz'63 model , 2012, 1212.4923.