similar to: Fast fourier transformation

Hello, I will try to explain the problem, sorry if it will be a little long... I'm using R to analyze results of cyclic mechanical testing, like this: - apply quasi-sinusoidal load - measure quasi-sinusoidal vertical and horizontal deformations (quasi-sinusoidal load means that load "should be" sinusoidal, but testing machine puts in some noise...) I enclose a sample of data at

Dear List, I am attempting to perform a harmonic analysis on a time series of snow depth, in which the annual curve is essentially asymmetric (i.e. snow accumulates slowly over time, and the subsequent melt occurs relatively rapidly). I am trying to fit a curve to the data, however, the actual frequency is unknown. I have been trying to follow the methods in Peter Bloomfields text

Dear R-help members, To whom it may concern, our research group is conducting a study to evaluate the predictive value of 24 hour blood pressure variability. We are looking for an R routine that performs a fast Fourier transform spectral analysis (with an output of the approximation function of the Fourier and estimates the validity of the model for the various harmonics). Thanks Vittorio

Dear R-helpers, I have time series data from 16 subjects and 2 treatment groups. The seasonal variation can be best described by two harmonics, I called the frequencies omega and omega2. I now want to test whether (1) the seasonal pattern differs between the treatments (some kind of overall test). If this is the case, (2) I want to conduct tests to find out whether the amplitude of the

Hi All, Here is the problem: I'm trying to generate a number of Fourier Descriptors figures for an experiment. All I need is that they are created within a loop and saved with sequential names (e.g., s1_1.png, s1_2.png etc..) in my directory. I created a nested loop with a counter for the different amplitudes for the actual shapes and a counter for the file names. This script: *count

Hello, In doing a series of non-linear estimations of a function which is a sum of a varying number of sinusoids, I would like to "autogenerate" the arguments needed by nls() depending on that number. For example, when there are two sinusoids: > nls( y ~ mu + A1 * cos(2*pi*f1*x - P1) + A2 * cos(2*pi*f2*x - P2), data = some.xy.data, start = list( mu=some.value0,

Hello, I'm having trouble connecting to an Apple Time Capsule's smb shares. The connection doesn't work, and with "dmesg" I see the following message, repeated every time I try: [26937.531511] CIFS VFS: RFC1001 size 39 bigger than SMB for Mid=4 [26937.531580] Bad SMB: : dump of 48 bytes of data at 0xffff880052832380 [26937.531615] 00000027 424d53ff 00000074 00018800

Hello, I try to synthesize harmonic functions with a subset of frequencies determined by fast fourier transform. I wrote two different functions, a looped version and a matrix multiplication version. As an example the looped version takes 5 sec and the matrix-version takes 3-4 sec (R 1.4, Athlon 1.2 GHz, 256 MB, Win ME), but the latter needs huge amount of memory due to the matrices. So, none of

Dear list, What on earth is spec.pgram() normalized too? If you would like to skip my proof as to why it's not normed too the mean squared or sum squared amplitude of the discrete function a[], feel free too skip the rest of the message. If it is, but you know why it's not exact in spec.pgram() when it should be, skip the rest of this message. The issue I refer herein refers only too a

Hello, I have done some research about breakpoints (I am not a statistician) and I found out about the breakpoint, strucchange and segmented packages in R allowing to find breakpoints assuming linear model. However, I would like to fit a periodic time series with a non linear (periodic) model, and I was wondering how I could find breakpoints for this model in R. Is it even possible ? My model

well if you want to find the spectral density aka what frequencies explain most of the variance then I would suggest the spectral density. This can be implemented with spec.pgram(). This is conducted with the fast fourier transform algorithm. a<-ts(data, frequency = 1) #make the time series with 365readings/365days ?spec.pgram and you should be able to take it from here This will

I am looking for a package to perform harmonic analysis with the goal of estimating the period of the dominant high frequency component in some mono-channel signals. I guess there are presumably a number of CRAN packages allowing for such analysis. However, my search with keywords was not successfull. It brought up a lot of Fourier miscellanea but nothing specifically geared for my needs. I would

Dear friends - I am trying to understand fda and working with the 2009 book from Springer. I run the scripts directly from a new installed fda library and include sessionInfo() below. This is from the script fdarm-ch09.R - I seem to have got not fda_2.2.8 but 2.2.7 - is that the problem? Where do I get .8 as I just reinstalled? Best wishes Troels Ring, Nephrology Aalborg, Denmark >

Hi John, Thanks for your reply. Yes, my output device is in 8-bit mode, same as my input mode. I'm actually working in char (8 bit) arrays. Is it necessary to work in signed short integers only? I changed all the short arrays in the example to char. Carine ----- Original Message ---- From: John Miles <jmiles@pop.net> To: carineliang@yahoo.com.sg; speex-dev@xiph.org Sent: Thursday,

Hi Dr. Viechtbauer, I'm doing meta-analysis using your package 'metafor'. I used the 'IRFT' to transform the incident rate. But when I tried to back-transform the summary estimates from function rma, I don't know what's the appropriate ti to feed in function transf.iirft. I searched and found your post about using harmonic mean for ni to back-transform the double

Hi, Can someone please help me with my problem below. Any suggestions is appreciated. thanks, Carine ----- Original Message ---- From: Carine Liang <carineliang@yahoo.com.sg> To: speex-dev@xiph.org; speex-dev@xiph.org Sent: Tuesday, 31 October 2006 1:05:49 PM Subject: [Speex-dev] Integrating speex with VideoNet application: Constant background noise Hi, I am developing a peer-to-peer

I did a fourier transform on a function in time domain to get the following functions in frequency domain (in latex): $Y_1[\omega] = \frac{1}{1-\phi_1 e^{-jw}}$ $Y_2[\omega] = \frac{1}{1-(\phi_1 + \phi_2)e^{-jw} +\phi_1\phi_2e^{-2jw}}$ How do I find the spectrum of this function for given $\phi_1$ and $\phi_2$ coefficients and in the discretization interval $w = [-\pi:.1*\pi: \pi]$? Then, how

Hello vorbis developer! I'm not very experienced in informatics, cause i'm only an audio engineer and sorry for my broken english but i have an idea... After the filterbank the maximum aplitude in each band decides about the nessesary bits, then the psychoacoustic model decides how much of the signal can be truncated without hearable noise. What do you think about quantising the

Dear R Users, I have a CO2 time series. I want to fit this series seasonal cycle and trend with fourth harmonic function, and then compute residuals. I am doing something like: file<-read.csv("co2data.csv") names(file) attach(file) fit<-lm(co2~1+time+I(time^2)+sin(2*pi*time)+cos(2*pi*time)+sin(4*pi*time)+cos(4*pi*time)+

I just finished testing and integrating Speex into our test project. Speex works excellent and sounds great for the bitrate. I have noticed, however, on cheaper microphones that Speex will produce loud static noise at high harmonics/amplitude in the sound. Is there some setting to prevent this static? I don't have this problem with various other manufacturer voice coders that I am using