signal-processing

Unlike the standard (and more challenging) de-blurring and super resolution scenarios, I have access to both the original (sharp) image G and it's blurred version B . I'm simply looking for the blur kernel h . So because B is taken using a real camera the relation is: B=G*h+N (where * denotes convolution and N is some additive noise) Naturally, this is an over-constrained problem since h is small in size compared to G and B and so every few pixels in the pair of images generate an equation on the entries of h . But what would be the simplest way to actually implement this? My thoughts so far:

I have and audio signal, which I read with Matlab, and use pwelch to get its PSD, here ist the code that I'm using [x,Fs] = audioread('audioFile.wav'); x= x(:,1) % mono [xPSD,f] = pwelch(x,hamming(512),16,1024,Fs); plot(f,xPSD); since the FS=96000 and I'm only interrested in Frequencies bellow 5khz, I would like to calculate the PSD only for the area, and also being able to adjust the resolution of the PSD ! any idea hwo to do that ! When calculating PSDs with pwelch , there is always a trade-off between spectral resolution, number of averages and the amount of data you need. My preferred way

I am trying to understand the FTT and convolution (cross-correlation) theory and for that reason I have created the following code to understand it. The code is Matlab/Octave, however I could also do it in Python. In 1D: x = [5 6 8 2 5]; y = [6 -1 3 5 1]; x1 = [x zeros(1,4)]; y1 = [y zeros(1,4)]; c1 = ifft(fft(x1).*fft(y1)); c2 = conv(x,y); c1 = 30 31 57 47 87 47 33 27 5 c2 = 30 31 57 47 87 47 33 27 5 In 2D: X=[1 2 3;4 5 6; 7 8 9] y=[-1 1]; conv1 = conv2(x,y) conv1 = 24 53 89 29 21 96 140 197 65 42 168 227 305 101 63 Here is where I find the problem, padding a matrix and a vector? How should I

I am doing a VoIP project on embedded device. I have built a sample using a 32bits MCU with a low grade audio codec. Now I found that there is echo issue on my device, that is I can hear what I said from the speaker. I have do some research and found that most appliaction use a DSP codec with acoustic echo cancellation feature. However, is it possible that I do the acoustic echo cancellation in the software, using my 32bits MCU? Can you adive the algorithm, or even source code:P, for doing acoustic echo cancellation? I know sophisticated method is not possible on a MCU, whereas a simple

Here is the scenario: using a spectrum analyzer i have the input values and the output values. the number of samples is 32000 and the sampling rate is 2000 samples/sec, and the input is a sine wave of 50 hz , the input is current and the output is pressure in psi. How do i calculate the frequency response from this data using MATLAB, using the FFT function in MATLAB. i was able to generate a sine wave, that gives out the the magnitude and phase angles, here is the code that i used: %FFT Analysis to calculate the frequency response for the raw data %The FFT allows you to efficiently estimate