spectrum

I am developing an app that get a source audio from mic in realtime, with no file storage. Basically, I use: mRecorder = new MediaRecorder(); mRecorder.setAudioSource(MediaRecorder.AudioSource.MIC); mRecorder.setOutputFormat(MediaRecorder.OutputFormat.THREE_GPP); mRecorder.setAudioEncoder(MediaRecorder.AudioEncoder.AMR_NB); mRecorder.setOutputFile("/dev/null"); My question is, how I can do a spectrum graphic from this realtime audio, with no files. It can be done? All post that I read are analyzing a buffered file. Thank you, and sorry for my english. yes it can be done. All you need is a fast

My question has to do with the physical meaning of the results of doing a spectral analysis of a signal, or of throwing the signal into an FFT and interpreting what comes out using a suitable numerical package, Specifically: take a signal, say a time-varying voltage v(t) throw it into an FFT (you get back a sequence of complex numbers) now take the modulus (abs) and square the result, i.e. |fft(v)|^2. So you now have real numbers on the y axis -- shall I call these spectral coefficients? using the sampling resolution, you follow a cookbook recipe and associate the spectral coefficients to

I need to identify a spectrum emitted from a light source (spectrometer). To do that, I need to convert each pixel to a wavelength. To overcome the problem that the RGB values do not have a single value, I will use a prism so that I will get an optical lattice. This way, I'm receiving a deployment of the spectrum, and the difference in the spectrum is only along the X axis. My question is, how do I convert the pixels to wavelengths and receive a plot of intensity as a function of wavelength. OpticsSoftware Late to the party. But here is an idea for accurately(close to scientific methodology)

I have found for several times the following guidelines for getting the power spectrum of an audio signal: collect N samples, where N is a power of 2 apply a suitable window function to the samples, e.g. Hanning pass the windowed samples to an FFT routine - ideally you want a real-to-complex FFT but if all you have a is complex-to-complex FFT then pass 0 for all the imaginary input parts calculate the squared magnitude of your FFT output bins (re * re + im * im) (optional) calculate 10 * log10 of each magnitude squared output bin to get a magnitude value in dB Now that you have your power

For my current project in C++ / Qt I need a library (LGPL is preferred) which can calculate a spectrogram from a signal ( basically an array of doubles ). I already use Qwt for the GUI part. Any suggestions? Thanks. It would be fairly easy to put together your own spectrogram. The steps are: window function (fairly trivial, e.g. Hanning) FFT (FFTW would be a good choice but if licensing is an issue then go for Kiss FFT or similar) calculate log magnitude of frequency domain components (trivial: log(sqrt(re * re + im * im)) David Cary "How do I create a frequency vs time plot?" lists several

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