  A method for measuring the spectrum of a density field by a discrete wavelet
space-scale decomposition (SSD) has been studied. We show how the power
spectrum can effectively be described by the father function coefficients (FFC)
of the wavelet SSD. We demonstrate that the features of the spectrum, such as
the magnitude, the index of a power law, and the typical scales, can be
determined with high precision by the FFC reconstructed spectrum. This method
does not require the mean density, which normally is poorly determined. The
problem of the complex geometry of observed samples can also be easily solved
because the basis are always orthogonal, regardless the geometry of the
samples. Using this method, we examine the spectra inferred from Ly$\alpha$
forests of both simulated and real samples. We find that 1.) the magnitude of
the 1-D spectra is significantly dfferent froma Poisson process; 2) the 1-d
spectra are flat on scales less than 5 h$^{-1}$ Mpc, and increase slowly at
larger ranges; 3.) the reconstructed 3-D spectra have about the same power as
the COBE normalized linear spectrum of the SCDM model on scales less than 40
h$^{-1}$ Mpc, but is larger than the SCDM model on scales larger than 40
h$^{-1}$ Mpc; 4) the magnitudes of high redshift ($z>2.51$) spectra generally
are larger than those of low redshift ($z<2.51$).
