This question already has answers here: Closed 12 years ago. Possible Duplicate: Reliable and fast FFT in Java
Using FFTW I have been computing the FFT of normalized .wav file data. I am a bit confused as to how I should normalise the FFT output, however. I have been using the method which seemed obvious to me
I am developing an application for an oscilloscope in c# .NET, I am drawing different kinds of waves (sine, square etc..) with the help of zedgraph control.
So far I\'ve implemented a gaussian blur filter entirely in the space domain, making use of the separability of the gaussian, that is, applying a 1D gaussian kernel along the rows and then along the c
I am creating a file to read in a certain number of .wav files, each of these corresponding to a musical note. I am performing an FFT on each of them and plotting them all on the same figure. However
Alright, so I am working on creating an Android audio visualization app. The problem is, what I get form the method getFft() doesn\'t jive with what google says it should produce. I traced the source
I want to plot the pitch of a sound into a graph. Currently I can plot the amplitude. The graph below is created by the data returned by getUnscaledAmplitude():
I\'m new to Fourier Transforms, so can someone explain what I need to do to replicate this behaviour in fftw:
I\'m looking to extract pitches from a sound signal. Someone on IRC just explained to me how taking a double FFT achieves this. Specifically:
I\'m messing around with Fourier transformations. Now I\'ve created a class that does an implementation of the DFT (not doing anything like FFT atm). This is the implementation I\'ve used:
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