similar to: fft and filtering puzzle

Hi, I'm in dire need of a fast fourier transformation for me stupid biologist, i.e. I have a heartbeat signal and would like to decompose it into pure sin waves, getting three vectors, one containing the frequencies of the sin waves, one the magnitudes and one the phases (that's what I get from my data acquisition software's FFT function). I'd be very much obliged, if someone

I'm not an engineer so I hope I'm using the correct terminology here. I have a recorded waveform that I want to apply low and high pass filters too, are tehre already R functions existing to do this or am I going to have to program my own? thanks for any pointers tom

I wrote a script that I anticipating seeing a spike at 10Hz with the function 10* sin(2*pi*10*t). I can't figure out why my plots do not show spikes at the frequencies I expect. Am I doing something wrong or is my expectations wrong? require(stats) layout(matrix(c(1,2,3), 3, 1, byrow = TRUE)) #SETUP n <- 256 #nextn(1001) gives next power 2 F <- 100 #Hz -50 to 50 Hz dt

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

I am in the process of dropping the TI DSP lib fft routines into the AEC. Currently, FFTWrap.c uses the USE_SMALLFT and USE_KISS_FFT to select between two packages of FFT routines. ] #ifdef USE_SMALLFT ... #elif defined(USE_KISS_FFT) ... #else #error No other FFT implemented #endif My guess is that every DSP and many other processors will have their own specific FFT and iFFT. What method

Dear Experts, I want to know if the KISS FFT in opus can be replaced with fast FFT. What are the implications & things to be taken care if this is done. Also, I saw in FFT code comments that in-line FFT not supported. Please let me know the reason for this. Thanks in advance. Regards, Mahantesh -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi, I am working on DSP module of Ne10. I see there are fixed-point and floating-point FFT inside Opus. Is fixed-point FFT only a fall back for CPU without VFP? On ARMv7-A and ARMv8-A, benchmark result shows that fixed-point (int32) and floating-point (float32) FFT have similar performance. I guess fixed-point version is not often used on these platforms. Is it worth the effort to NEON-optimize

On 29 April 2015 at 17:22, Timothy B. Terriberry <tterribe at xiph.org> wrote: > > Viswanath Puttagunta wrote: >> >> This patch series is follow up on work I posted on [1]. >> In addition to what was posted on [1], this patch series mainly >> integrates Fixed point FFT implementations in NE10 library into opus. >> You can view my opus wip code at [2]. >

Hi R-users: I want to know if there is an easy way to obtain a Fourier Transform form a vector or an array (just like fft does), but with a more density base. I mean, if I have a vector of 512 of length, I want the Fourier Transform to be 1024, or 2048, etc, in length (de u domain). Or should I modify the fft C code to do that? If I want to modify the precision of the fft function, which

Hi I have made a R function 'convolve2' for convolution of two real valued vectors based on Rs 'convolve' with option type="open" - see below. (exp.length and irf.length are variables set in another part of the program) I wish to implement the function convolve2 in C and use it in a function used from R with .Call - e.g. I need to call fft in C. All I can find in the

The book "Numerical Recipes in Fortran77" by Press, Teukolsky, Vetterling and Flannery describes a way to "pack" the even and odd coordinates of a real vector "R" into a complex vector "C" of half the length. Then using various FFT symmetries, they extract the FFT of "R" from the FFT of "C" which is half the length of "R",

Hi, I am a brand new user of R and I have a really stupid problem: I am having troubles applying fft on 2D matrices. I import a data file of 256*256 elements with read.table (it is actually a grey scale image, the corresponding data file being generated with Matlab), and I find that the fft can be applied on one single column of data, but not on one row. (Error message: Error in fft(z, inverse)

Hello, I'm new to R (using it since about two weeks), but absolutely a fan of it from the beginning on. :-) Best tool for working with data I found. :-) I tried using the fft() and other funcitons for analysing time series. What I would be glad to have, would be a convenient way to display the complex result of a fft in a way, that real and imaginary parts each use an axis for themselves,

The characteristic function is the inverse Fourier transform of the distribution function. The characteristic function of a normaly distributed random variable is exp(-t^2/2). x=seq(-2,2,length=100) fft(pnorm(x),inverse=T)/length(x) exp(-x^2/2) Why aren't the inverse fft and the mentioned function the same? Thanks for help, Thomas

Hello! thank you for your efforts creating R! While preparing the next lessons I found that I had to multiply with 1/length(x) by hand if I want to get the inverse Fouriertransform. The help states it will do it by itself. Version R-0.60.1, Linux Seems to be pretty easy to correct either the fft or :-) the help(fft)! Cu Detlef Detlef Steuer Universitaet Dortmund ///////

I have a a simple function that generates a time series square wave: genseq <- function() { x <- numeric(4*365) s <- seq(as.Date("2005-01-01"), as.Date("2008-12-31"), by="month") ob <- as.vector(s[c(10,22,34,46)] - as.Date("2005-01-01")) oe <- as.vector(s[c(11,23,35,47)] - as.Date("2005-01-01")) for(.index in 1:length(ob))

Hi everyone, I have profiled Opus on AArch64. I just run opus_demo with some pcm files. Following is time proportion of FFT with different bitrate. Bitrate | Time cost by FFT/iFFT 24kb/s | 15% 48kb/s | 15% 96kb/s | 13% Any comment? I want some data close to real application, any suggestion? Thanks, Phil Wang -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi everyone, I am working on Ne10 project. Ne10 provides NEON optimized FFT routines that are much faster (compared to those without NEON), on most ARMv7-A and all ARMv8-A devices. How about integrate it into Opus? I am not familiar with configure script, but I find "Optinal Packages" in it. If we provides --with-ne10-fft option, the one extra thing that users need to do is to

Dear all, Before I can get into serious Fourier analysis of Radon time-series I am practising with 24hour and 24.8hour sinusoids to assist with my interpretation of signals ittributed to tidal input to Radon time series. I am stuck. I have tried researching this to no avail. I am awating a book that should describe fourier transforms in detail and another one that should discuss the R

Hi! I am using the fft() function the base package to transform some 1d signal. If I use this standar fucntion I get a very huge first fourier coeficient. I think this dues to the handling of the borders of the signal. Usually in fft especially in image processing the signal is simulated to be continuous by adding the signal several times periodically. My question is, is there some function