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Full-Text Articles in Dynamic Systems
Interpreting Shift Encoders As State Space Models For Stationary Time Series, Patrick Donkoh
Interpreting Shift Encoders As State Space Models For Stationary Time Series, Patrick Donkoh
Electronic Theses and Dissertations
Time series analysis is a statistical technique used to analyze sequential data points collected or recorded over time. While traditional models such as autoregressive models and moving average models have performed sufficiently for time series analysis, the advent of artificial neural networks has provided models that have suggested improved performance. In this research, we provide a custom neural network; a shift encoder that can capture the intricate temporal patterns of time series data. We then compare the sparse matrix of the shift encoder to the parameters of the autoregressive model and observe the similarities. We further explore how we can …
Application Of Symplectic Integration On A Dynamical System, William Frazier
Application Of Symplectic Integration On A Dynamical System, William Frazier
Electronic Theses and Dissertations
Molecular Dynamics (MD) is the numerical simulation of a large system of interacting molecules, and one of the key components of a MD simulation is the numerical estimation of the solutions to a system of nonlinear differential equations. Such systems are very sensitive to discretization and round-off error, and correspondingly, standard techniques such as Runge-Kutta methods can lead to poor results. However, MD systems are conservative, which means that we can use Hamiltonian mechanics and symplectic transformations (also known as canonical transformations) in analyzing and approximating solutions. This is standard in MD applications, leading to numerical techniques known as symplectic …