Wavelets of non-stationary time series

I'm new to wavelets, but like what I've read so far i.t.o. "de-noising" a time series. I would like to apply a wavelet transform to a 70 length crude oil price window not just because of its denoising capabilities, but also if I can get a new series that is closely normally dsitributed. Is this possible using wavelets (1)?

Crude prices are generally non-stationary, so I thought perhaps I can use a complex gaussian wavelet (I've read-up on the toolbox but not much further help). I'm not really sure how to apply wavelets which is probably my first stumbling block. If the first question (1) is a "yes" that it can be transformed to a normally distributed series how do I use wavelets. I've typed waveinfo('cgau') which says cgau(x) = C_{p}e^{-ix}e^{-x^2} which just gives me the function. How do I actually apply this to my CrudePrices = [70,1]. Do I have to write my own loop, or is there already a function in the signal processing toolbox?

I would appreciate anyones knowledge or advice on this and apologies for the long-winded email but just some direction would be great.

[Muhammad Nabiil Aujeemuddee]

hello, have you been able to run this; I'm stuck as well. Thanks