signal-processing

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 3 years ago . Need to find if there is a open source project for audio signal processing, just as we have openCV for image processing. Thanks 回答1: In my course for the more technical part, we were introduced to signal processing, we had to use Octave with the audio package and gnu plot for plotting. For the fun part of the

问题 Gaussian smoothing is a common image processing function, and for an introduction of Gaussian filtering, please refer to here. As we can see, one parameter: standard derivation will determine the shape of Gaussian function. However, when we perform convolution with Gaussian filtering, another parameter: the window size of Gaussian filter should also be determined at the same time. For example, when we use fspecial function provided by MATLAB, not only the standard derivation but also the

问题 Trying to use portaudio to record some data, then use an algorithmic filter to change the recorded voice and then play it back. I've verified a lot of it (coming from example) but I'm quite new to C and I think in my filter implementation I've done something silly. #if LOW_PASS { float RC = 1.0/(CUTOFF*2*3.14); float dt = 1.0/SAMPLE_RATE; float alpha = dt/(RC+dt); float filteredArray[numSamples]; filteredArray[0] = data.recordedSamples[0]; for(i=1; i<numSamples; i++){ filteredArray[i] =

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . I'm looking for a book similar to "Introduction to Algorithms" by Thomas Cormen geared towards DSP algorithms. Is there anything as thorough as Cormen on the DSP market? EDIT I should say I'm looking for a book that's analogous to The Joy of Cooking. 回答1: Disclaimer - I am not familiar with the Cormen book so I

问题 I'm looking for how to draw the sound waves according to music. I want waves like this image here is some discussion about displaying Waves from music WaveForm on IOS rendering a waveform on an iphone audio waveform visualisation with iPhone Github Example Links https://github.com/gyetvan-andras/cocoa-waveform https://github.com/benalavi/waveform https://github.com/JingWZ/WaveView https://github.com/gyetvan-andras/cocoa-waveform https://github.com/ioslovers/ATTabandHoldAudioRecord https:/

问题 I am studying image processing these days and I am a beginner to the subject. I got stuck on the subject of convolution and how to implement it for images. Let me brief - there is a general formula of convolution for images like so: x(n1,n2) represents a pixel in the output image, but I do not know what k1 and k2 stand for. Actually, this is what would like to learn. In order to implement this in some programming language, I need to know what k1 and k2 stand for. Can someone explain me this

问题 My app. is displaying the peak frequency of input sound in RPM .. i have array of doubles contains the samples in time domain. audioRecord.read(buffer, 0, 1024); Then i did FFT on it . transformer.ft(toTransform); using this class Here then i got the max magnitude of complex values which are the results of FFT // block size = 1024 double magnitude[] = new double[blockSize / 2]; for (int i = 0; i < magnitude.length; i++) { double R = toTransform[2 * i] * toTransform[2 * i]; double I =

问题 How can I get the correct frequency vector to plot using the FFT of MATLAB ? My problem: N = 64; n = 0:N-1; phi1 = 2*(rand-0.5)*pi; omega1 = pi/6; phi2 = 2*(rand-0.5)*pi; omega2 = 5*pi/6; w = randn(1,N); % noise x = 2*exp(1i*(n*omega1+phi1))+4*sin(n*omega2+phi2); h = rectwin(N).'; x = x.*h; X = abs(fft(x)); Normally I'd do this : f = f = Fs/Nsamples*(0:Nsamples/2-1); % Prepare freq data for plot The problem is this time I do not have a Fs (sample frequency). How can I do it correctly in this

问题 I want to make a program that detects the note that is being played in front of the microphone. I am testing the FFT function of Naudio, but with the tests that I did in audacity it seems that FFT does not detect the pitch correctly. I played an C5, but the highest pick was at E7. I changed the first dropdown box in the frequency analysis window to "enchanced autocorrelation" and after that the highest pick was at C5. I googled "enchanced autocorrelation" and had no luck. 回答1: The highest

问题 I use matplotlib for a signal processing application and I noticed that it chokes on large data sets. This is something that I really need to improve to make it a usable application. What I'm looking for is a way to let matplotlib decimate my data. Is there a setting, property or other simple way to enable that? Any suggestion of how to implement this are welcome. Some code: import numpy as np import matplotlib.pyplot as plt n=100000 # more then 100000 points makes it unusable slow plt.plot