DSP using MATLAB 示例Example3.7】的更多相关文章

代码: % Discrete-time Signal x1(n) % Ts = 0.0002; n = -25:1:25; nTs = n*Ts; Fs = 1/Ts; x = exp(-1000*abs(nTs)); Ts = 0.001; n = -5:1:5; nTs = n*Ts; Fs = 1/Ts; x = exp(-1000*abs(nTs)); % Analog Signal Dt = 0.00005; t = -0.005:Dt:0.005; xa = x * sinc(Fs*…
代码: % Analog Signal Dt = 0.00005; t = -0.005:Dt:0.005; xa = exp(-1000*abs(t)); % Discrete-time Signal Ts = 0.0002; n = -25:1:25; x = exp(-1000*abs(n*Ts)); % Discrete-time Fourier Transform %Wmax = 2*pi*2000; K = 500; k = 0:1:K; w = pi*k/K; % index ar…
代码: % Analog Signal Dt = 0.00005; t = -0.005:Dt:0.005; xa = exp(-1000*abs(t)); % Continuous-time Fourier Transform Wmax = 2*pi*2000; K = 500; k = 0:1:K; % index array k for frequencies W = k*Wmax/K; % freqency between 0 and +pi, [0,pi] axis divided i…
代码: % Discrete-time Signal x1(n) : Ts = 0.0002 Ts = 0.0002; n = -25:1:25; nTs = n*Ts; x1 = exp(-1000*abs(nTs)); figure('NumberTitle', 'off', 'Name', 'Example3.23 Reconstructed From x1(n)'); set(gcf,'Color','white'); subplot(2,1,1); stairs(nTs*1000,x1…
代码: b = [0.0181, 0.0543, 0.0543, 0.0181]; % filter coefficient array b a = [1.0000, -1.7600, 1.1829, -0.2781]; % filter coefficient array a m = 0:length(b)-1; l = 0:length(a)-1; % index arrays m and l K = 500; k = 0:1:K; % index array k for frequenci…
代码: % Discrete-time Signal x2(n) Ts = 0.001; n = -5:1:5; nTs = n*Ts; Fs = 1/Ts; x = exp(-1000*abs(nTs)); % Analog Signal Dt = 0.00005; t = -0.005:Dt:0.005; xa = x * sinc(Fs*(ones(length(n),1)*t - nTs'*ones(1,length(t)))) ; % check error = max(abs(xa…
上代码: subplot(1,1,1); b = 1; a = [1, -0.8]; n = [0:100]; x = cos(0.05*pi*n); y = filter(b,a,x); figure('NumberTitle', 'off', 'Name', 'Input and Output sequence'); set(gcf,'Color','white'); subplot(2,1,1); stem(n,x); title('Input sequence'); xlabel('n'…
上代码: w = [0:1:500]*pi/500; % freqency between 0 and +pi, [0,pi] axis divided into 501 points. H = exp(j*w) ./ (exp(j*w) - 0.9 * ones(1,501)); magH = abs(H); angH = angle(H); realH = real(H); imagH = imag(H); %% ---------------------------------------…
用到的性质 代码: n = -5:10; x = sin(pi*n/2); k = -100:100; w = (pi/100)*k; % freqency between -pi and +pi , [0,pi] axis divided into 101 points. X = x * (exp(-j*pi/100)) .^ (n'*k); % DTFT of x % signal decomposition [xe,xo,m] = evenodd(x,n); % even and odd…