similar to: floor curve question (whitening filter)

I've made a block diagram of the encoder because I tried to find out, how it works http://stoffke.freeshell.65535.net/ogg/block.html Although there are specifiation docs, that give very detailed information about single aspects of the encoding (or decoding) , I'm missing documenations that give a more general overview, about how the encoder works. (Vorbis Illuminated seems a bit

Hi guyz, I have run my algorithm in R (see http://pastebin.com/q84Tujfg) and got the following error: Error in ar.ols(x, aic = aic, order.max = order.max, na.action = na.action, : 'order.max' must be < 'n.used' I am pretty sure, that the error comes from the NeweyWest function in line 45, as the NeweyWest function uses the ar.ols() function for pre whitening. Does anyone

Hi R users, I am doing cross correlation analysis on 2 time series (call them y-series and x-series) where I need the use the model developed on the x-series to prewhiten the yseries.. Can someone point me to a function/filter in R that would allow me to do that? Thanks in advance for any help! -- View this message in context:

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Hello, Vorbis uses codebooks, for example to do vectorquantization and huffman-encoding. My question is - are all these codebook dynamicly generated ("trained") or are there also static codebooks used ? If yes, what specific tasks are these 2 types used for, during encoding ? Thanks Stoffke <p>--- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project

Hello, I have a few questions about the block size in ogg vorbis 1. The allowed blocksizes are powers of two between 64 and 8192 Samples. As I understood , there are fixed sizes for long and short blocks . The encoder can pick any allowed value for long blocks and onother value, that must be smaller or equal to the first one, for short blocks. On which base does the encoder choose the size for

Hello I had an idea about judging the quality of ogg vorbis (or any other lossy codec) I took a wave-file and encoded it to ogg. Then decoded ogg to wav and inverted it's phase. When mixing the original wav with the phase-inverted decoded ogg-file, any identic parts of compressed and uncompressed audio should be eliminated. Of course there's always a "rest" of sound because

I've made block diagram of the encoder because I tried to find out, how it works http://stoffke.freeshell.65535.net/ogg/block.html Although there are specifiation docs, that give very detailed information about single aspects of the encoding (or decoding) , I'm missing documenations that give a more general overview, about how the encoder works. (Vorbis Illuminated seems a bit outdated,

I found this sentence in the Ogg format specs: http://www.xiph.org/ogg/vorbis/doc/vorbis-spec-res.html "A residue vector may represent spectral lines, spectral magnitude, spectral phase or hybrids as mixed by channel coupling." But where does the spectral phase information come from ? AFAIK MDCT doesn't provide any phase information. And in OGG-encoding, MDCT is taking place a few

Hello, I wanted to find out more about square polar mapping, cause that whole stuff is a bit tricky - to me - and not so easy to understand. Searching the web did't get me any results, so I wonder what the background of square polar mapping is. Is it derived from some mathematical publications or just the result of a brilliant intuition of a Vorbis programmer ? ;) Thanks. Stoffke

I have a time series with a one year lag, ar=0.5. The series has some interesting events that disappear when the series is whitened (i.e., fitting an AR process and looking at the residuals). I'd like to remove the autocorrelation in stages to see the effect on the time series. Is there a way to specify the autocorrelation term while fitting an AR process? For instance, given the following:

Hi, Can you please help me? Whenever I try to run f.ica.fmri.gui(), R crashes. In the GUI, I selected an *.img file and I checked the 'Create mask' box and I typed a name for the object and then I press 'Start' button. Then in the R Console window it said 'Reading...Whitening', but after the Whitening message an error window popped up and then R crashed. Did I do something

Hi all, I have two time series that I would like to correlate but as they are autocorrelated, I am "pre-whitening" them first by fitting ARIMA models, then correlating their residuals....as described in https://onlinecourses.science.psu.edu/stat510/?q=node/75 However, http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm discusses some issues with ARIMA in R. In particular, for issue 2, if

Hi all, I am whitening my data: # code begins N <- 300 M <- 2 x <- matrix(data=rnorm(N*M, 0, 3)-10, ncol=M, nrow=N) y <- matrix(c(1,-2,-2,1), ncol=M, nrow=M) z <- data.frame(x %*% y) colnames(z) <- c('x','y') par(mfrow=c(1,3)) plot(z, pch=5, col="blue") whiten <- function(x) { (x-mean(x))/sd(x) } zz <- transform(z, x=whiten(x), y=whiten(y))

On Mon, Aug 11, 2014 at 12:45:27PM +0530, Amit Shah wrote: > > What's the suggested value for rng->quality, though, for virtio-rng > that I can use to ensure the kthread starts? > > Should I use the 700 (70%) as proposed in the original patchset? I'm > not exactly sure how that value will be used as well.. There is no such thing as a suggested value, every number

On Mon, Aug 11, 2014 at 12:45:27PM +0530, Amit Shah wrote: > > What's the suggested value for rng->quality, though, for virtio-rng > that I can use to ensure the kthread starts? > > Should I use the 700 (70%) as proposed in the original patchset? I'm > not exactly sure how that value will be used as well.. There is no such thing as a suggested value, every number

Hi All, I have a doubt in Vorbis coding. It is said, the encoder subtracts the floor from the MDCT of the data to get the residue. But in the decoder, the 'dot product' of of the floor and residue is done to get back the data. If subtraction is done at one end, addition should be done at the other end. What exactly is 'dot product'? Can you name the function in the decoder

Hello, I'm currently using auto.arima to verify the order of my arima model. I would like to use the model to conduct an intervention analysis. The problem is that, when I include a step function in auto.arima, by including a binary variable in "xreg", the arima order that auto.arima gives is different from when I don't include it. From my understanding, the

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