Matlab Tutorial: Digital Image Processing 6. Low pass filter. (Edge Detection, Sharpening) A high-pass filter can be used to make an image appear sharper. Image processing using matlab to find. Will u plz send me some Research papers on the topic 'CRACK DETECTION AND TECH USED' WITH. Now u can use matlab code.

I'm designing a project in which an array is passed through (QAM) modulator, and then do carrier modulation, make it playable with the command, then demodulate it back for QAM demodulation. Firstly, I have used the standard way of QAM modulation: M = 16; x = randint(5000, 1, M); y = modulate(modem.qammod(M), x); Then, I wrote my own carrier modulation function: function [out] = carriermodulation(x) fs = 16000; T = 1.0 / 4000; fc = 8000; Q = real(x); I = imag(x); t = 0:T:(size(x))*T; C1 = zeros(size(x), 1); C2 = zeros(size(x), 1); for i = 1:size(x) C1(i) = I(i)*sin(2*pi*(fc)*t(i)); C2(i) = Q(i)*sin(2*pi*fc*t(i) + pi/2); end out = C1 + C2; No problem so far. But when I was done with my demodulation function, I found that the result is different from the original value (the QAM modulator output). Function [out] = carrierdemodulation(x) fs = 16000; T = 1.0 / 4000; fc = 8000; t = 0:T:(size(x))*T; A1 = zeros( size(x), 1); A2 = zeros( size(x), 1); for i = 1:size(x) A1(i) = x(i)*sin( 2*pi*(fc)*t(i)); A2(i) = x(i)*cos( 2*pi*(fc)*t(i)); end A1 = sqrt(A1); A2 = sqrt(A2); out = A1 + A2; I think my modulation part is right. The only problem I think I have is I don't have a (LPF) for the demodulation. And I should not calculate A1 and A2 directly. How do I to add an LPF to my demodulation code such that the output is the same as the original?

You need a low-pass filter at the receiver after coherent demodulation, that's right. But there's also a problem with your modulation.

In your example, the symbol rate Rs is less than the angular carrier frequency w_c which potentially causes overlapping of spectra at the receiver. Consequently, reconstruction of the information signal will be impossible. Additionaly, in your example fc * T = 2. That means that the argument of the sine function is an integer multiple of 2pi and therefore always zero.

What you need is an impulse shaper (can be implemented as a low-pass filter) at the transmitter with bandwidth w_g >Installer Aplikasi Persediaan 2011 Silverado. = R/2. It should be a so-called lowpass. The carrier frequency must satisfy w_c >w_g. I've written a script that does impulse shaping, modulation, demodulation, filtering and sampling, so that the transmitted signal can be reconstructed.

First we define the parameters, create random bits and do the mapping as you've already done. Than a very simple impulse response for impulse shaping is used, namely a rectangular impulse. In the real world we're going from digital to analog domain here, but as this is a computer model, we represent the analog signal by a discrete one with sampling frequency f_s. The impulse shaper is simple, because it just repeats each sample L times. M = 16;% QAM order fs = 16000;% Sampling frequency in Hz Ts = 1/fs;% Sampling interval in s fc = 1000;% Carrier frequency in Hz (must be fg) Rs = 100;% Symbol rate Ns = 20;% Number of symbols x = randint(Ns, 1, M); y = modulate(modem. English And American Literature Michael Meyer Pdf Printer there. qammod(M), x); L = fs / Rs;% Oversampling factor% Impulse shaping y_a = reshape(repmat(y', L, 1), 1, length(y)*L); Now modulation. I used a carrier frequency that satisfies the above conditions: it's higher than the signal bandwidth and can still be represented with the sampling frequency used.%% Modulation I = real(y_a); Q = imag(y_a); t = 0: Ts: (length(y_a) - 1) * Ts; C1 = I.* sin(2*pi * fc * t); C2 = Q.* cos(2*pi * fc * t); s = C1 + C2; Demodlation is straightforward.%% Demodulation r_I = s.* sin(2*pi * fc * t); r_Q = s.* -cos(2*pi * fc * t); To remove the spectral tributaries at 2f_c after demodulation a low-pass filter is required. I used the MATLAB to create the filter and part of the following code.