  Gravitational-wave searches for the merger of compact binaries use
matched-filtering as the method of detecting signals and estimating parameters.
Such searches construct a fine mesh of filters covering a signal parameter
space at high density. Previously it has been shown that singular value
decomposition can reduce the effective number of filters required to search the
data. Here we study how the basis provided by the singular value decomposition
changes dimension as a function of template bank density. We will demonstrate
that it is sufficient to use the basis provided by the singular value
decomposition of a low density bank to accurately reconstruct arbitrary points
within the boundaries of the template bank. Since this technique is purely
numerical it may have applications to interpolating the space of numerical
relativity waveforms.
