  This note considers the multidimensional unstructured sparse recovery
problems. Examples include Fourier inversion and sparse deconvolution. The
eigenmatrix is a data-driven construction with desired approximate eigenvalues
and eigenvectors proposed for the one-dimensional problems. This note extends
the eigenmatrix approach to multidimensional problems. Numerical results are
provided to demonstrate the performance of the proposed method.
