Reply by dbd April 23, 20092009-04-23
On Apr 23, 1:25 pm, Rune Allnor <all...@tele.ntnu.no> wrote:
>... > > The objective of using windows in PSD estimation > is to reduce the variance of the PSD estimate, compared > to the 'raw' periodogram.
For some reason you seem stuck on PSD estimation and the techniques for estimating stationary PSDs. Most windowing is not done to reduce the variance of the estimation of stationary PSDs. Most places where windowing is used have time varying PSDs, discrete tones and transients. These are applications like music, voice, active sonar, passive sonar and machinery vibration analysis processing. The choice of window is often made to control bias due to discrete tones in the estimation of other discrete tones and dynamically varying power spectra.
> > The Blackman-Tukey method, which in the form everybody > quotes
Actually, not many people are quoting the Blackman-Tukey method these days. Indications of those who do include academic positions, age and ownership of old texts. The methods in the Welch form won the hearts and minds of most instrument designers and data analysts with the advent (or at least anticipation of) fast DFT implementation. That change was on its way by the mid 1970's. harris didn't invent it, but he is a frequently referenced reporter of the events and correct usage at the time.
> ...
The small frequency kernel characteristic of proper DFT windows was presented by Blackman and Tukey in the Bell System Technical Journal in 1958 (and the Dover reprints of it from 1958 and on which you mention Papoulis referring to). The description by harris is better and freely available. The Nuttall paper is another one that is not protected by US copyright. The Nuttall paper is concerned entirely with the windows that are correctly representable by small kernels in the frequency domain. The Nuttall paper also includes corrections to the harris paper, in particular with regard to the 2 digit rounded 3 term (5 point kernel) Blackman and the optimized 4 term Blackman- harris. Dale B. Dalrymple
Reply by Rune Allnor April 23, 20092009-04-23
On 23 Apr, 21:27, Martin Eisenberg <martin.eisenb...@udo.edu> wrote:
> Rune, > > I spent today at the library and took the chance to look at the books > you cited, their window use and rationale. What I found is that you > have been drawing on the wrong context. Yes, the texts feature even- > symmetry windows prominently -- but those live in the *lag domain* > and are applied to correlation functions whereas *time-domain* > windowing was at issue in this thread.
And in another sub-thread we discussed spatial domain. Is there a relevant difference? The maths of window functions and the DFT doesn't change with the context. Well, unless you quietly change from 1D signals to 2D signals, which happened in a different sub-thread.
> You actually mentioned > correlation functions in one post but I didn't catch on earlier to > the conflation of PSD estimation on one hand and harmonic analysis > (which concerns nonstationary but mostly deterministically conceived > signals) on the other, though Dale repeatedly used the latter term. > > Some specific notes on the books I had available now: > > - Papoulis: Probability, Random Variables and Stochastic Processes, > 1991 > > Discusses discrete-time forms seemingly only in sec. 13-3 (method of > windows), which is about lag domain. I couldn't find the "large N" > approximation you noted, but
I quoted the page when I first mentioned the Papolis book. In my copy it is at the bottom of page 456 and start of page 457, the last couple of lines before eq. 13-77. In the last un-numbered equation before eq. 13-75 he uses the CT form w(tau) = 1/pi*sin(pi tau/M) + |1-|tau|/M|*cos (pi tau/M) (*) and then he makes a general statement about DT domain windows w[m] in eq. 13.77, w[m] = w(Mm/L), m=0,...,L (**) where w() is the CT domain window function. I must admit that I only skimmed the passage at first reading. Now that you made me have a closer look at the details, it seems that if you use the (*) form for w() in (**), you end up with an N-1-period expression: cos(pi*tau/M) = cos((pi Mm/L)/M) = cos(pi m/L), m = 0,...,L
> it would be interesting to know the > precise context and what compelled Papoulis to introduce it
He mentions, below eq. 13-74: "If M is large in the sense that S(w-a) ~ S(w) for |a| <= 1/M, we can use the approximation..." I have no idea what the rationale is, but my impression is that Papoulis often wrote very terse, almost incomprehensable summaries of earlier texts. Presumably it would be useful to review the original 1959 book by Blackman and Tukey, which Papoulis refers to.
> despite > the need for qualification.
Well, if you think Papoulis is wrong I'm sure you can come up with an argument to explain why?
> - Oppenheim, Schafer: Digital Signal Processing, 1975 > > This introduces lag-domain windows on -(M-1)..M-1, then moves to > time-domain 0..M-1 in sec. 11.4.3/11.6.1 (Welch method) but with no > mention of how to assign w(n) now. They give no pertinent inline > references either.
Well, that book came out 3 years befor Harris' paper, so I'd be slightly surprised if they quoted it...
> - Bendat, Piersol: Random Data. Analysis and Measurement Procedures, > 1986 (an older edition than you cited) > > Eq. 11.117 in fact gives the Hann window in periodic form, > &#4294967295; &#4294967295;1 - cos^2(pi*n/N), &#4294967295;n=0..N-1, > as the only time-domain example and goes on to say,
The 2000 edition uses a form that mixes continuous-time and discrete-time notation in eq. 11.121, page 432: u_h (tau) = 1/2(1+cos(pi t/ tau_max)) = 1/2 (1+cos(pi r/m)), r = 0,1,2,...,m This is the N-1-period form.
> "See References > [harris, Nuttall] for discussions of other tapering operations." To > my mind that's not passing mention as you called it but heavy > reliance. (The other paper -- Nuttall, "Some Windows with Very Good > Sidelobe Behavior", IEEE Trans. ASSP, v29-1, Feb. 1981 -- itself > cites harris for an overview like, I believe, most presentations of a > new window do.) > > Now, as far as I noticed, none mentioned the argument about all raw > bins contributing to each smoothed PSD point that you presented as > crucial. Was it really your own ad-hoc explanation of what's going > on, or do you have a quote to that effect?
Well, I haven't seen any explanation to that effect, but this question was the fact that made me question if the difference between the N-pt FD convolution and the 3-pt FD convolution has more significant relevance than mere FLOP counts. Just to be clear about where I start from: Every single author on PSD estimation emphasizes that the periodogram is a lousy PSD estimator because of the variance being large and independent of the number of samples. Multiplying by window functions in time domain corresponds to convoluting with window spectra in frequency domain. The N-pt convolution computes the PSD estimate as the weighted average of *all* periodogram coefficients. The 3-pt convolution computes the PSD estimate as the weighted average of only 3 periodogram coefficients. I assume everybody agrees so far. The question I asked was this: Convolving with the 3-pt kernel is certainly faster than the N-pt kernel, if windowing is computed in frequency domain. But then the question is why none of the authors on PSD estimation have commented on this. Is there a reason why none of the textbook authors even mention this 'fast; computation? The follow-up question, then, is to ask what the purpose of the N-pt convolution kernel is, and see if the 3-pt kernel maybe misses its mark: The objective of using windows in PSD estimation is to reduce the variance of the PSD estimate, compared to the 'raw' periodogram. The Blackman-Tukey method, which in the form everybody quotes (no, I haven't seen the original writings) uses the N-1-period window form that corresponds to convolving with an N-pt kernel. Computing the PSD as the average of *all* periodogram coefficients makes a lot of sense to me when the objective is to significantly reduce the variance compared to the periodogram. The N-pt convolution kernel achieves the stated goal. My naive view is that averaging a mere 3 periodogram coefficients will not make a big difference when the objective is to come up with a PSD estimate that has a significantly lower variance than the periodogram. As far as I am concerned, that's a very good reason to use the N-pt convolution kernel in PSD estimation. Rune
Reply by Martin Eisenberg April 23, 20092009-04-23
Rune,

I spent today at the library and took the chance to look at the books 
you cited, their window use and rationale. What I found is that you 
have been drawing on the wrong context. Yes, the texts feature even-
symmetry windows prominently -- but those live in the *lag domain* 
and are applied to correlation functions whereas *time-domain* 
windowing was at issue in this thread. You actually mentioned 
correlation functions in one post but I didn't catch on earlier to 
the conflation of PSD estimation on one hand and harmonic analysis 
(which concerns nonstationary but mostly deterministically conceived 
signals) on the other, though Dale repeatedly used the latter term.

Some specific notes on the books I had available now:

- Papoulis: Probability, Random Variables and Stochastic Processes, 
1991

Discusses discrete-time forms seemingly only in sec. 13-3 (method of 
windows), which is about lag domain. I couldn't find the "large N" 
approximation you noted, but it would be interesting to know the 
precise context and what compelled Papoulis to introduce it despite 
the need for qualification.

- Oppenheim, Schafer: Digital Signal Processing, 1975

This introduces lag-domain windows on -(M-1)..M-1, then moves to 
time-domain 0..M-1 in sec. 11.4.3/11.6.1 (Welch method) but with no 
mention of how to assign w(n) now. They give no pertinent inline 
references either.

- Bendat, Piersol: Random Data. Analysis and Measurement Procedures, 
1986 (an older edition than you cited)

Eq. 11.117 in fact gives the Hann window in periodic form,
   1 - cos^2(pi*n/N),  n=0..N-1,
as the only time-domain example and goes on to say, "See References 
[harris, Nuttall] for discussions of other tapering operations." To 
my mind that's not passing mention as you called it but heavy 
reliance. (The other paper -- Nuttall, "Some Windows with Very Good 
Sidelobe Behavior", IEEE Trans. ASSP, v29-1, Feb. 1981 -- itself 
cites harris for an overview like, I believe, most presentations of a 
new window do.)

Now, as far as I noticed, none mentioned the argument about all raw 
bins contributing to each smoothed PSD point that you presented as 
crucial. Was it really your own ad-hoc explanation of what's going 
on, or do you have a quote to that effect?


Martin

-- 
Quidquid latine scriptum est, altum videtur.
Reply by dbd April 18, 20092009-04-18
On Apr 18, 5:11 am, Rune Allnor <all...@tele.ntnu.no> wrote:
> On 18 Apr, 03:27, dbd <d...@ieee.org> wrote: > > > On Apr 17, 12:33 pm, Rune Allnor <all...@tele.ntnu.no> wrote: > > > >... > > > Virtually all the textbook issues I have found on > > > the window functions, use window functions of length > > > N and cosine terms with period N-1. This means that > > > all the coefficients of the DFT of the window function > > > are non-zero. > > > ... > > > Rune > > > Your conclusion is incorrect. It is difficult for anyone to help you > > with this error because we don't all have access to your 'texts' > > OK. I have mentioned them briefly throughout this thread, > but here are those I can find just by scanning my bookshelf > quickly: > > Book{papoulis, > author = {Papoulis, {A.}}, > title = {Probability, Random Variables and > Stochastic Processes}, > publisher = {McGraw-Hill International Editions}, > year = 1991, > edition = {third}, > > } > > @Book{kay-book, > author = {Kay, {S.M.}}, > title = {Modern Spectral Estimation, Theory \& Application}, > publisher = {Prentice Hall}, > SERIES = {Signal Processing Series}, > year = 1988, > } > > @Book{proakis-manolakis-3, > author = {Proakis, {J.G.} and Manolakis, {D. G.}}, > title = {Digital Signal Processing, > Principles, Algorithms and Applications}, > publisher = {Prentice Hall}, > edition = {3rd}, > year = 1996, > } > > @Book{bendat-piersol, > author = {Bendat, {J.S.} and Piersol,{A.G.}}, > title = {Random Data. Analysis and Measurement Procedures}, > publisher = {Wiley}, > edition = {3rd.}, > year = 2000 > > } > > @Book{oppenheim-schafer-75, > author = {Oppenheim, {A.V} and Schafer, {R.W.}}, > title = {Digital Signal Processing}, > publisher = {Prentice Hall}, > year = 1975 > > } > > @Book{oppenheim-schafer-99, > author = {Oppenheim, {A.V} and Schafer, {R.W.}}, > title = {Discrete-Time Signal Processing}, > publisher = {Prentice Hall}, > edition = {2nd}, > year = 1999 > > } > > @book{antoniou, > author = {Antoniou, {A.}}, > title = {Digital Signal Processing -- Signals, Systems and Filters}, > publisher = {McGraw-Hill}, > year = 2006 > > } > > There might be at least one of these available to you. > Except for Papoulis, who defends the N-period form with > N being large, all of these use the N-1-period form. > It N-1 vs N form is not my 'discovery'. I'm stating what > is de facto standard 'gospel' in the DSP community. > > I know I have a copy of both the Leland B. Jackson 1989 book, > and a Dover edition of Hamming's book somewhere. Would you like > me to dig them up and check them as well? >
Why do you need to try to distract with a list of references we don't all have access to instead of talking with respect to a source available to all?
> > and > > their context to see if there is any relevance to your discovery of > > N's and N-1's. > > Just to be totally clear about what I we are talking about, > in an earlier post I wrote that > > I use the term > 'N-period window' for N-length window with divisor N > in the cosine terms, and 'N-1-period window' for N-length > windows with divisor N-1 in the cosine terms. > > So a window > > w[n] = 0.5 + 0.5 cos(2pin/N), n = 0,...,N > > is on the N-1-period form since the window is of length N+1. > It's not sufficient to just scan the formula for the period > of the cosine; you need to find the length of the window as > well.. > > I am sure this comes as a surprise to you (honestly, no > irony or sarcasm here), but *you* are the one who introduce > the off-the-beaten-path arguments here. Which is why I have > pushed so hard for you to come up with an argument other > than 'Harris said so.' > > > There is a source that has been referenced in this > > thread that explains this issue with regard to windows for harmonic > > analysis. If you are honest about learning you would consider actually > > reading it. It is available to everyone here. You can tell us where > > you think it is wrong there and we can all view what you are talking > > about. That's why I provided an accessible reference. > > The problem is that your one, old, journal reference > is at odds with every textbook I have available. Every > single text - apart form Papoulis - use the N-1-period > form everywhere. >
.> Imagine yourself in my place, just having read the textbooks .> and having no personal reason to trust the writings of any .> one particular person. Imagine the readers of this thread who read the three examples of advantageous windowing in the frequency domain that I posted in this thread on April 4 and you deny the existence of. Why should anyone be surprised that you haven't found what you aren't honest enough to look for?
> > Wouldn't you ask the same question? > > > Matlab will help you > > Here is a direct implementation of Proakis & Manolakis' > Hann window. It's taken from table 8.1 in their 3rd > edition (p. 626). The only change I've made is to > center the window on (M-1)/2, not 0: > > %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% > M = 9; > > h = zeros(1,M); % Window is of length M > > for n=0:M-1 > h(n+1) = 0.5+0.5*cos(2*pi*(n-(M-1)/2)/(M-1)); > % Cosine term is of period M-1 > end > %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% > > The output is: >
.> ans = .> .> 0 4.0000 .> 0.1464 2.3349 .> 0.5000 0.2103 .> 0.8536 0.0607 .> 1.0000 0.0154 .> 0.8536 0.0154 .> 0.5000 0.0607 .> 0.1464 0.2103 .> 0 2.3349 .> .> As you can see, no non-zero coefficients in .> the spectrum. Actually,
>> fft(h)'
ans = 4.0000 -2.1941 + 0.7986i 0.1611 - 0.1352i 0.0303 - 0.0525i 0.0027 - 0.0152i 0.0027 + 0.0152i 0.0303 + 0.0525i 0.1611 + 0.1352i -2.1941 - 0.7986i Your example h is correct for a 9 point filter design window. For the DFT case, the circularity of the process (or 'periodic' in Matlab's terminolgy) makes the final element of h wrap to the first position. The 'FFT-even' application of this window is the 8 point window h(1:8) and:
>> fft(h(1:8))'
ans = 4 -2 0 0 0 0 0 -2 Lots of zero terms. The point of 'FFT-even' appears in the left column on page 52 of the harris paper. I'm not going to retype it or paraphrase it here. It is accessible to all of us. Try agreeing or disagreeing with something we all can view. It's nice you have texts. Let's see if you can read what the rest of us can read.
> > > tell the difference between > > windows applied to filter design and windows for > > DFT application > > So there *is* a difference? Why, then, isn't this > mentioned by any of the authors who write textbooks > on PSD estimation? Not to mention general DSP texts > that cover both filters and PSD estimation? > > If you, as it seems, have so strong opinions about the > N-period form being 'correct' and the N-1-period form > being 'wrong', then you might want to have a word > with the authors and editors of what are the de facto > standard textbooks on DSP. Both those on general DSP > and those on PSD estimation. > > Rune
I don't know the earliest usage of the small frequency domain kernel windowing approach. It goes back at least to Blackman and Tukey in the Bell System Technical Journal in 1958. (And the Dover reprints in 1959 and on) Maybe Von Hann's implementation was in the frequency domain. Dale B. Dalrymple
Reply by Rune Allnor April 18, 20092009-04-18
On 18 Apr, 03:27, dbd <d...@ieee.org> wrote:
> On Apr 17, 12:33 pm, Rune Allnor <all...@tele.ntnu.no> wrote: > > >... > > Virtually all the textbook issues I have found on > > the window functions, use window functions of length > > N and cosine terms with period N-1. This means that > > all the coefficients of the DFT of the window function > > are non-zero. > > ... > > Rune > > Your conclusion is incorrect. It is difficult for anyone to help you > with this error because we don't all have access to your 'texts'
OK. I have mentioned them briefly throughout this thread, but here are those I can find just by scanning my bookshelf quickly: Book{papoulis, author = {Papoulis, {A.}}, title = {Probability, Random Variables and Stochastic Processes}, publisher = {McGraw-Hill International Editions}, year = 1991, edition = {third}, } @Book{kay-book, author = {Kay, {S.M.}}, title = {Modern Spectral Estimation, Theory \& Application}, publisher = {Prentice Hall}, SERIES = {Signal Processing Series}, year = 1988, } @Book{proakis-manolakis-3, author = {Proakis, {J.G.} and Manolakis, {D. G.}}, title = {Digital Signal Processing, Principles, Algorithms and Applications}, publisher = {Prentice Hall}, edition = {3rd}, year = 1996, } @Book{bendat-piersol, author = {Bendat, {J.S.} and Piersol,{A.G.}}, title = {Random Data. Analysis and Measurement Procedures}, publisher = {Wiley}, edition = {3rd.}, year = 2000 } @Book{oppenheim-schafer-75, author = {Oppenheim, {A.V} and Schafer, {R.W.}}, title = {Digital Signal Processing}, publisher = {Prentice Hall}, year = 1975 } @Book{oppenheim-schafer-99, author = {Oppenheim, {A.V} and Schafer, {R.W.}}, title = {Discrete-Time Signal Processing}, publisher = {Prentice Hall}, edition = {2nd}, year = 1999 } @book{antoniou, author = {Antoniou, {A.}}, title = {Digital Signal Processing -- Signals, Systems and Filters}, publisher = {McGraw-Hill}, year = 2006 } There might be at least one of these available to you. Except for Papoulis, who defends the N-period form with N being large, all of these use the N-1-period form. It N-1 vs N form is not my 'discovery'. I'm stating what is de facto standard 'gospel' in the DSP community. I know I have a copy of both the Leland B. Jackson 1989 book, and a Dover edition of Hamming's book somewhere. Would you like me to dig them up and check them as well?
> and > their context to see if there is any relevance to your discovery of > N's and N-1's.
Just to be totally clear about what I we are talking about, in an earlier post I wrote that I use the term 'N-period window' for N-length window with divisor N in the cosine terms, and 'N-1-period window' for N-length windows with divisor N-1 in the cosine terms. So a window w[n] = 0.5 + 0.5 cos(2pin/N), n = 0,...,N is on the N-1-period form since the window is of length N+1. It's not sufficient to just scan the formula for the period of the cosine; you need to find the length of the window as well.. I am sure this comes as a surprise to you (honestly, no irony or sarcasm here), but *you* are the one who introduce the off-the-beaten-path arguments here. Which is why I have pushed so hard for you to come up with an argument other than 'Harris said so.'
> There is a source that has been referenced in this > thread that explains this issue with regard to windows for harmonic > analysis. If you are honest about learning you would consider actually > reading it. It is available to everyone here. You can tell us where > you think it is wrong there and we can all view what you are talking > about. That's why I provided an accessible reference.
The problem is that your one, old, journal reference is at odds with every textbook I have available. Every single text - apart form Papoulis - use the N-1-period form everywhere. Imagine yourself in my place, just having read the textbooks and having no personal reason to trust the writings of any one particular person. Wouldn't you ask the same question?
> Matlab will help you
Here is a direct implementation of Proakis & Manolakis' Hann window. It's taken from table 8.1 in their 3rd edition (p. 626). The only change I've made is to center the window on (M-1)/2, not 0: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% M = 9; h = zeros(1,M); % Window is of length M for n=0:M-1 h(n+1) = 0.5+0.5*cos(2*pi*(n-(M-1)/2)/(M-1)); % Cosine term is of period M-1 end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% The output is: ans = 0 4.0000 0.1464 2.3349 0.5000 0.2103 0.8536 0.0607 1.0000 0.0154 0.8536 0.0154 0.5000 0.0607 0.1464 0.2103 0 2.3349 As you can see, no non-zero coefficients in the spectrum.
> tell the difference between > windows applied to filter design and windows for > DFT application
So there *is* a difference? Why, then, isn't this mentioned by any of the authors who write textbooks on PSD estimation? Not to mention general DSP texts that cover both filters and PSD estimation? If you, as it seems, have so strong opinions about the N-period form being 'correct' and the N-1-period form being 'wrong', then you might want to have a word with the authors and editors of what are the de facto standard textbooks on DSP. Both those on general DSP and those on PSD estimation. Rune
Reply by dbd April 17, 20092009-04-17
On Apr 17, 12:33 pm, Rune Allnor <all...@tele.ntnu.no> wrote:
>... > Virtually all the textbook issues I have found on > the window functions, use window functions of length > N and cosine terms with period N-1. This means that > all the coefficients of the DFT of the window function > are non-zero. > ... > Rune
Your conclusion is incorrect. It is difficult for anyone to help you with this error because we don't all have access to your 'texts' and their context to see if there is any relevance to your discovery of N's and N-1's. There is a source that has been referenced in this thread that explains this issue with regard to windows for harmonic analysis. If you are honest about learning you would consider actually reading it. It is available to everyone here. You can tell us where you think it is wrong there and we can all view what you are talking about. That's why I provided an accessible reference. Matlab will help you tell the difference between windows applied to filter design and windows for DFT application:
>> % FIR window design vector >> s = hann(8,'symmetric')
s = 0 0.1883 0.6113 0.9505 0.9505 0.6113 0.1883 0
>> fft(s)/8
ans = 0.4375 -0.2402 - 0.0995i 0.0189 + 0.0189i 0.0026 + 0.0063i 0 0.0026 - 0.0063i 0.0189 - 0.0189i -0.2402 + 0.0995i
>> % DFT window vector for harmonic analysis >> p = hann(8,'periodic')
p = 0 0.1464 0.5000 0.8536 1.0000 0.8536 0.5000 0.1464
>> fft(p)/8
ans = 0.5000 -0.2500 0.0000 0 0 0 0.0000 -0.2500
>>
That's how it works under Matlab's fft definition. Dale B. Dalrymple
Reply by Rune Allnor April 17, 20092009-04-17
On 17 Apr, 18:30, Eric Jacobsen <eric.jacob...@ieee.org> wrote:
> On Fri, 17 Apr 2009 00:34:07 -0700 (PDT), Rune Allnor > > > > > > <all...@tele.ntnu.no> wrote: > >On 17 Apr, 05:02, dbd <d...@ieee.org> wrote: > >> On Apr 16, 10:04 am, Rune Allnor <all...@tele.ntnu.no> wrote: > > >> > ... > >> > But that's *design*. I still haven't seen any reason to do > >> > the *computations* in frequency domain. > > >> > Rune > > >> In this thread on April 4, Eric Jacobsen suggested an example. In the > >> last paragraph of my post on that day I suggested three. Why haven't > >> you commented on these? Those who merely read this thread have seen > >> reasons posted. > > >Well, I'm probably screwed up by having made a living > >by *applied* DSP (as opposed to academics or research) > >for too long. > > The example I gave was practical. &#4294967295;I learned that doing fast > correlations for synthetic aperture radar processing.
Where did you mention it? I can only find one other post of yours through Google groups: http://groups.google.no/group/comp.dsp/msg/d0280ff1d4149ecd?hl=no
> I haven't followed the entire argument, so I don't know how much the > context has shifted,
Well, a quick recap of my questions is found here: http://groups.google.no/group/comp.dsp/msg/98f74d795425172a?hl=no Virtually all the textbook issues I have found on the window functions, use window functions of length N and cosine terms with period N-1. This means that all the coefficients of the DFT of the window function are non-zero. First of all, I showed that there are problems with this approach for certain standard problems involving window functions: http://groups.google.no/group/comp.dsp/msg/1426fa4aff6a60cd?hl=no I then proceeded to ask what the purpose is for using the 3pt frequency domain form of the kernel, that is, cosine terms with period N, given the problems.
> but if you're convolving/correlating a fixed > reference function against a frequency-domain vector (i.e., using fast > correlation), it's trivial to apply the FD weighting function to the > pre-stored reference function. It then costs NO additional > computation and you get the weighting function essentially for free.
Everything is pre-computed and stored in, what, spatial domain?
> In the SAR context the weighting function was critical in controlling > the target sidelobes and resolution in the output image, which was in > the domain after the next transform.
I am sure it was. What was the decider? The type of window (Hamming, Hann, Blackman,...) or the size of of the FD kernel for a given type of window? In other words, did you compare the results from the 3-pt kernel with no kernel and N-pt kernel for a given type of window? Rune
Reply by Eric Jacobsen April 17, 20092009-04-17
On Fri, 17 Apr 2009 00:34:07 -0700 (PDT), Rune Allnor
<allnor@tele.ntnu.no> wrote:

>On 17 Apr, 05:02, dbd <d...@ieee.org> wrote: >> On Apr 16, 10:04 am, Rune Allnor <all...@tele.ntnu.no> wrote: >> >> >> >> > ... >> > But that's *design*. I still haven't seen any reason to do >> > the *computations* in frequency domain. >> >> > Rune >> >> In this thread on April 4, Eric Jacobsen suggested an example. In the >> last paragraph of my post on that day I suggested three. Why haven't >> you commented on these? Those who merely read this thread have seen >> reasons posted. > >Well, I'm probably screwed up by having made a living >by *applied* DSP (as opposed to academics or research) >for too long.
The example I gave was practical. I learned that doing fast correlations for synthetic aperture radar processing. I haven't followed the entire argument, so I don't know how much the context has shifted, but if you're convolving/correlating a fixed reference function against a frequency-domain vector (i.e., using fast correlation), it's trivial to apply the FD weighting function to the pre-stored reference function. It then costs NO additional computation and you get the weighting function essentially for free. In the SAR context the weighting function was critical in controlling the target sidelobes and resolution in the output image, which was in the domain after the next transform. Eric Jacobsen Minister of Algorithms Abineau Communications http://www.ericjacobsen.org Blog: http://www.dsprelated.com/blogs-1/hf/Eric_Jacobsen.php
Reply by Rune Allnor April 17, 20092009-04-17
On 17 Apr, 13:39, Martin Eisenberg <martin.eisenb...@udo.edu> wrote:
> Rune Allnor wrote: > > - What was the objective with using the N-pt kernel?
> > I also argued why the 3-pt kernel is at least > > pedagoically problematic in the context of FIR filter > > design,
> Where noone was proposing its use to begin with.
Do you agree with me in that the N-period forms are obsolete for FIR filter design? That whatever advantage they might offer over N-1-period forms are taken care of at least as well by e.g. Parks-McClellan designs? I assume your answer is 'yes', so that we can focus on PSD estimation below.
> > and does not serve the useful purpose in the > > context of PSD estimation. > > You did not demonstrate that. Much of your effort arguing would have > been better spent on finding out that the period-(N-1) Hann window's > transform bins outside the three central points contain less than > 0.5% of the total energy at N=8 and this decreases as O(1/N^2). How > significant is those values' contribution to a spectral weighted > average going to be for transform sizes that yield useful resolution?
Actually, I have no idea. I just observe that every textbook author - except one - who writes on the subject uses the N-1-period forms of the windows. The one exception is Papoulis, who states the N-period form with the proviso 'If N is large' (Papoulis: "Probability, Random Variables, and Stochastic Processes", 3rd ed, 1991, p. 456). Presumably, since he explicitly mentions large N, he would use some other form for small N. Having said that - both your comment about realtive significance and Papoulis' comment about large N makes sense if one is talking about numerical accuracies e.g. in fixed- point arithmetics. In these cases the difference between N-period window and the N-1-period window would be lost in arithmetic inaccuracies. That's an argument for the simplification which is straight- forward and easy to understand. However, they do not quite require Nobel laureate levels of skills to come up with. Since no one have mentioned these very basic arguments so far in the discussion, it makes me believe they are not used as support for selecting the N-period forms. Dale mentioned he wouldn't create confusion by inaccuaretly paraphrase arguments, but the arguments above are so simple that they can not possibly what he had in mind. So what is it Harris has seen that no one else have? The paper has been out there for more than 30 years, but is at best mentioned in passing by authors on spectrum estimation like Kay, and Bendat and Piersol, and not at all by Papoulis? If the paper is as important - except for purely historical reasons - as some seem to think, why aren't the results mentioned in the textbooks? Rune
Reply by jim April 17, 20092009-04-17

Rune Allnor wrote:
>why > use the 3pt kernel at all? Even more computations are saved > by just skipping them alltogether and using the raw > spectrum, right?
So you are again saying that one should never use a Hann window? Maybe the OP wants to find out if your advice is sound or not? Seems like that would be a good reason to use the frequency domain 3 pt kernel. You continue to ignore the fact that because the OP is using a sliding DFT it is computationally more efficient and easier to modify his algorithm to include a Hann window in the frequency domain than to do it in the time domain. Whether he needs a window at all is something the OP can ponder when he reaches the point where he can make a comparison. -jim
> > The *only* argument against this line of reasoning is > that 'using the 3pt kernel serves some purpose other > than just saving computations compared to the Npt kernel'. > > It is this purpose I try to understand what might be. > > Rune