On Thursday, February 28, 2013 10:32:08 PM UTC+13, Riheen wrote: > TideMan <email@example.com> wrote in message <firstname.lastname@example.org>... > > > On Thursday, February 28, 2013 9:30:12 AM UTC+13, Riheen wrote: > > > > Hi , > > > > > > > > I am doing EEG signal processing. Suppose, my data is sampled with 500Hz. So, according to Nyquist theorem there is 250 hz spectrum. I filtered the signal 0-64 Hz. I need 0-8Hz band. Now how much decomposition level is required?? 3 or 5?? > > > > > > I find it easier to work in timescales, not frequencies: > > > dt=1/500; seconds > > > Level 1: 2*dt > > > Level 2: 2^2*dt > > > Level 3: 2^3*dt > > > etc > > > > > > Then, > > > 8 Hz => 1/8 s = 2^n*dt > > > 2^n=500/8 > > > n=log2(500/8)=5.9 > > > so you need to decompose to level 6, and the approximation will be 0 to 8Hz (approximately). > > > > > > Note, however, that these timescales are not exact. > > > In fact for ocean waves and using mother wavelet 'db5' (which fits ocean waves very nicely), I find (from zero crossing analysis) that the times scales go like: > > > Level 1: 1.5*2*dt > > > Level 2: 1.5*2^2*dt > > > Level 3: 1.5*2^3*dt > > > etc > > > whence: > > > n=log2(500/8/1.5)=5.4 > > > > Hi TideMan, > > thanks for tour reply. you said i need level 6. But i told that, i filtered the signal 0-64 Hz . I think, now i need only 3 levels for 0-8 Hz coefficients. Here it is- > > 1st level: detail(33-63), approx.(0-32) > > 2nd level: detail(17-32), approx.(1-16) > > 3rd level: detail(9-16), approx(0-8) > > > > Here, you can see after 3 levels i can get 0 to 8 hz approximate coefficients. My data sampling frequency is 500Hz. > > Is there any problem in my concept?? If so please explain.
When you "filtered", did you also decimate? If not, then what I wrote applies. If you did, then the sampling frequency is not 500 Hz, but something else: 64 Hz perhaps? BTW, there's no need to filter before wavelet decomposition. Wavelet decomposition does a fine job of that itself.