Dynamic mode decomposition for analysis of time-series data
Ivan Maruŝiĉ
Abstract
Since its publication in 2010, the paper by Schmid ( J. Fluid Mech. , vol. 656, 2010, pp. 5–28) has wielded considerable influence, an impact we examine here. That seminal work introduced dynamic mode decomposition, a method for performing flow-field spectral analysis of snapshot sequences of data. As a data-driven approach aimed at uncovering spatial and temporal patterns or modes within datasets, its applicability has extended far beyond fluid mechanics, reaching into a wide array of fields.
Topics & Concepts
Dynamic mode decompositionComputer scienceSnapshot (computer storage)Time seriesMode (computer interface)Series (stratigraphy)Statistical physicsSpectral analysisFlow (mathematics)Fluid dynamicsFluid mechanicsAlgorithmData miningMechanicsPhysicsGeologyMachine learningSpectroscopyQuantum mechanicsPaleontologyOperating systemModel Reduction and Neural NetworksFluid Dynamics and Vibration AnalysisFluid Dynamics and Turbulent Flows