  We present a template-free method of estimating pulse height of
micro-calorimeter signals based on principal component analysis (PCA). The
method is shown to improve the resolution on a simulated dataset by 25\%
compared to the standard filtering technique that uses the averaged pulse as an
estimation for the signal template. This technique is useful for reconstruction
of pulses in micro-calorimeters with a high degree of pulse-shape variation
where finding the correct signal templates is difficult.
