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Gram Schmidt Process Algorithm
%ECE24063 t1 = 0:0.01:1; t2 = 1:0.01:2; t3 = 2:0.01:3; t = [t1,t2,t3]; s1 = ones(1,length(t1)); s2 = ones(1,length(t...
Gram Schmidt Process Algorithm
%ECE24063 t1 = 0:0.01:1; t2 = 1:0.01:2; t3 = 2:0.01:3; t = [t1,t2,t3]; s1 = ones(1,length(t1)); s2 = ones(1,length(t...
3 days 前 | 0
已回答
How do I obtain a "normal" PCM Signal?
x=random('norm',0,1,1,500); figure; stem(x) title("Gaussian signal") xlabel("Number of random variables") ylabel("amplitude...
How do I obtain a "normal" PCM Signal?
x=random('norm',0,1,1,500); figure; stem(x) title("Gaussian signal") xlabel("Number of random variables") ylabel("amplitude...
3 days 前 | 0
已回答
how can i quantize the normal distribution using uniform PCM?
fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); subplot(2,1,1) stem(t,x) title("Original signal") title("t") xlabel("x"...
how can i quantize the normal distribution using uniform PCM?
fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); subplot(2,1,1) stem(t,x) title("Original signal") title("t") xlabel("x"...
3 days 前 | 0
已回答
how can i quantize the normal distribution using uniform PCM?
fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); N = 8; [quant,qlev] = uni(x,N); [quant,code] = uniformpcm1(x,N); P...
how can i quantize the normal distribution using uniform PCM?
fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); N = 8; [quant,qlev] = uni(x,N); [quant,code] = uniformpcm1(x,N); P...
3 days 前 | 0
已回答
how can i quantize the normal distribution using uniform PCM?
%ECE24063 fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); subplot(2,1,1) plot(t,x) title("sine signal") xlabel("time") y...
how can i quantize the normal distribution using uniform PCM?
%ECE24063 fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); subplot(2,1,1) plot(t,x) title("sine signal") xlabel("time") y...
3 days 前 | 0
已回答
how can i quantize the normal distribution using uniform PCM?
%ECE24063 fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); subplot(2,1,1) plot(t,x) title("sine signal") xlabel("time") y...
how can i quantize the normal distribution using uniform PCM?
%ECE24063 fs = 1000; t = 0:1/fs:2; x = sin(2*pi*5*t); subplot(2,1,1) plot(t,x) title("sine signal") xlabel("time") y...
3 days 前 | 0
已回答
how can i quantize the normal distribution using uniform PCM?
%ECE24063 function [quant,code] = uniformpcm1(x,N) x_max = max(x); x_min = min(x); N = 8; delta = (x_max - x_min)/N...
how can i quantize the normal distribution using uniform PCM?
%ECE24063 function [quant,code] = uniformpcm1(x,N) x_max = max(x); x_min = min(x); N = 8; delta = (x_max - x_min)/N...
3 days 前 | 0
已回答
how can i quantize the normal distribution using uniform PCM?
%ECE24063 function [quant,qlev] = uni(x,N) x_max = max(x); x_min = min(x); N = 8; delta = (x_max - x_min)/N; R =...
how can i quantize the normal distribution using uniform PCM?
%ECE24063 function [quant,qlev] = uni(x,N) x_max = max(x); x_min = min(x); N = 8; delta = (x_max - x_min)/N; R =...
3 days 前 | 0
已回答
Colour quantization, uniform quantization
x = random('norm',2,sqrt(5),1,10000); subplot(3,1,1) stem(x) title("Gaussian signal") xlabel("time") ylabel("amplitude") ...
Colour quantization, uniform quantization
x = random('norm',2,sqrt(5),1,10000); subplot(3,1,1) stem(x) title("Gaussian signal") xlabel("time") ylabel("amplitude") ...
3 days 前 | 0
已回答
Colour quantization, uniform quantization
% Uniform Quantization of Piecewise Signal t1 = -1:0.01:0; t2 = 0.01:0.01:1; x1 = t1 + 1; x2 = t2 - 1; t = [t1 t2]; ...
Colour quantization, uniform quantization
% Uniform Quantization of Piecewise Signal t1 = -1:0.01:0; t2 = 0.01:0.01:1; x1 = t1 + 1; x2 = t2 - 1; t = [t1 t2]; ...
3 days 前 | 0
已回答
plot autocorrelation
%ECE24063 clc; clear; close all; % Parameters Am = 5; fm = 2e3; fc = 10 * fm; t = 0:1e-6:2e-3; % Message signal ...
plot autocorrelation
%ECE24063 clc; clear; close all; % Parameters Am = 5; fm = 2e3; fc = 10 * fm; t = 0:1e-6:2e-3; % Message signal ...
4 days 前 | 0
