  We introduce a filter-construction method for pulse processing that differs
in two respects from that in standard optimal filtering, in which the average
pulse shape and noise-power spectral density are combined to create a
convolution filter for estimating pulse heights. First, the proposed filters
are computed in the time domain, to avoid periodicity artifacts of the discrete
Fourier transform, and second, orthogonality constraints are imposed on the
filters, to reduce the filtering procedure's sensitivity to unknown baseline
height and pulse tails. We analyze the proposed filters, predicting energy
resolution under several scenarios, and apply the filters to high-rate pulse
data from gamma-rays measured by a transition-edge-sensor microcalorimeter.
