Optimal Approximation of Snapshot Vectors using Proper Orthogonal Decomposition

The proper orthogonal decomposition (POD) method provides an optimal way to approximate a finite set of snapshot vectors in a Hilbert space using a low-dimensional subspace. The POD basis vectors are obtained as the eigenvectors of a specific linear operator associated with the snapshot data.