Code, Data, and Results for Numerical Experiments in "Interpolatory Approximations of PMU Data: Dimension Reduction and Pilot Selection"
Code, Data, and Results for Numerical Experiments in "Interpolatory Approximations of PMU Data: Dimension Reduction and Pilot Selection"
This archive contains the companion codes, data, and computed results for the paper: S. Reiter, M. Embree, S. Gugercin, V. Kekatos; "Interpolatory Approximations of PMU Data: Dimension Reduction and Pilot Selection" which implements numerical experiments involving interpolatory matrix approximations of Phasor Measurement Unit (PMU) data for wide-area monitoring of electrical power systems.
- Courant Institute of Mathematical Sciences United States
- New York University United States
Electrical Power Systems, MATLAB, Interpolatory Matrix Decompositions, Event Monitoring, Low-Rank Matrix Decompositions, Sparse Reconstruction, Discrete Empirical Interpolation Method (DEIM), Numerical Linear Algebra, Phasor Measurement Unit (PMU) Data, Disturbance Event Detection
Electrical Power Systems, MATLAB, Interpolatory Matrix Decompositions, Event Monitoring, Low-Rank Matrix Decompositions, Sparse Reconstruction, Discrete Empirical Interpolation Method (DEIM), Numerical Linear Algebra, Phasor Measurement Unit (PMU) Data, Disturbance Event Detection
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