functionX=myFFT(x)%MYFFT Compute the FFT of a signal using a recursive algorithm.% X = M...
plot(f, abs(X)); title('FFT of the Signal'); xlabel('Frequency (Hz)'); ylabel('Magnitude'); 通过这些步骤,您可以在MATLAB中成功进行FFT分析。FFT的结果可以帮助您理解信号的频率特性,并为进一步分析提供依据。 FFT分析有什么应用? 快速傅里叶变换(FFT)在多个领域有着广泛的应用。以下是一些常见的应用...
xlabel('t (milliseconds)') ylabel('X(t)') % Compute the Fourier transform of the signal. Y = fft(X); % Compute the two-sided spectrum P2. Then compute the single-sided spectrum P1 based on P2 and the even-valued signal length L. P2 = abs(Y/L); P1 = P2(1:L/2+1); P1(2...
参考 快速傅里叶变换 - MATLAB fft - MathWorks 中国clear all; Fs = 1000; % Sampling frequency T = 1/Fs; % Sampling period L = 1500; % Length of signal t = (0:L-1)*T; % Time vector S = 0.7*sin(2*pi*50*…
matlab代码见下: function F=fft_hust syms x; T=20; n=10; %谐波的阶数 t=0:0.01:80; %如果创建-1,+1的方波直接调用square即可 %50是50%占空比 f=max(7*square(pi*0.1*t,50),3);%创建方波最大值是1,最小值是0 plot(t,f); grid on; ...
% To use the fft function to convert the signal to the frequency domain, % first identify a new input length that is the next power of 2 from the original signal length. % This will pad the signal X with trailing zeros in order to improve the performance of fft. ...
在MATLAB 中尝试 尝试此示例 使用傅里叶变换求噪声中隐藏的信号的频率分量。 指定信号的参数,采样频率为 1 kHz,信号持续时间为 1.5 秒。 Fs = 1000;% Sampling frequency T = 1/Fs;% Sampling period L = 1500;% Length of signal t = (0:L-1)*T;% Time vector ...
3; %幅度 3 MaxS=A1+A2+A3; %信号幅度的最大值 signal=A1*sin(2*pi*f1*t) +A2*sin(2*pi*f2*t) +A3*sin(2*pi*f3*t) ; X=fft(signal, len) ; %傅里叶变换 magX=abs(X) ; %信号的幅度 angX=angle(X) ; %信号的相位 Y=magX. *exp(1i*angX) ; %信号的频域表示 y=ifft(Y, ...
i map the frequeny axes of the first fft into time axes at that time, the amplitude of fft remains in the frequency domain only. I am just changing the axes from frequency to time. So when i take the second fft so indirectly i am taking the fft two times of the original signal?
L = 1500; % Length of signal t = (0：L-1)*T; % Time vector % Form a signal con...