In this article a new method to estimate optimum filter Length in line
ar prediction is described, Linear prediction was used to enhance reso
lution of a spectrum. In particular, the dependence of prediction erro
r on filter length has been studied, With calculations of simulated sp
ectra it is shown that the prediction error falls rapidly when the fil
ter length attains its optimum value. This effect is quite pronounced
when the spectrum has a good signal-to-noise ratio and the modified co
variance method is used to calculate prediction filter coefficients, T
he method is illustrated with applications to real Raman spectra.