Re: Generating 1/f^2 and 1/f^3 noise

On Mar 16, 2:38 pm, "Andor" <andor.bari...@xxxxxxxxx> wrote:

2. You define the L2-norm of a vector (on page 3) as

||x||_L2 = sqrt(1/N sum_{k=1}^N x_k^2).

This is the first time I see the factor sqrt(1/N) included in the
definition of the L2-norm.

i've seen it. it's "root mean square" instead of "root sum of
squares". both are norms. they both satisfy the four axiomatic
properties of norms (the 4th is the triangle inequality). i think the
normalization is useful when you want to make comparisons with
different N.

4. On page 1 you write:

"
Filtering in the frequency
domain requires the entire data sequence yn to
be computed and stored in advance, and if many long
sequences are required the storage becomes prohibitive.
"
If I understand you correctly you are saying that frequency domain
filtering can only be applied to a single data block. This is not
quite correct.

i would delete the word "quite".

Using overlap methods (overlap-save or overlap-add),
y_n can be constructed from short blocks.

i would say "shortER blocks". the blocks can be pretty large (like 5
or 10 times the FIR length) if OLA or OLS is optimized to minimize the
computational cost per sample.

r b-j

.

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