function y=testfft() %输入f1、f2、取样点数N0 f1=input('请输入f1 '); f2=input('请输入f2 '); N0=input('请输入N0 '); %补零 x0=[0:0.001:(N0-1)*0.001]; x=1.5*cos(2*pi*f1*x0)+cos(2*pi*300*x0)+0.5*cos(2*pi*f2*x0); m=nextpow2(length(x)); N=2^m; if length(x)<N x=[x,zeros(1,N-length(x))];%有修改 end %内置函数FFT运算结果保存到y0中 y0=fft(x); %反序 change=bin2dec(fliplr(dec2bin([1:N]-1,m)))+1; y=x(change); %蝶形 for s=1:m Nr=2^s;u=1; WN=exp(-i*2*pi/Nr); for j=1:Nr/2 for k=j:Nr:N kp=k+Nr/2; g=y(kp)*u; y(kp)=y(k)-g; y(k)=y(k)+g; end u=u*WN; end end save data y y0; end 代码解释

这段代码是一个 MATLAB 函数，实现了离散傅里叶变换（DFT）的计算。具体来说，它输入三个参数：信号的两个频率 f1 和 f2，以及采样点数 N0。首先，根据这些参数，生成一个由连续的正弦波信号组成的向量 x。如果 x 的长度不是 2 的幂次方，则在其末尾补零，使其长度为 2 的幂次方。然后，将 x 进行 FFT 变换得到频域信号 y0，再按照 DIF（Decimation in Frequency）蝶形算法对 y0 进行重新排序得到频域信号 y，并将 y 和 y0 的值保存在 data.mat 文件中。最后，函数返回 y。

相关问题

function y=testfft() %输入a、b、取样点数c a=input('请输入f1 '); b=input('请输入f2 '); c=input('请输入N0 '); %补零 x0=[0:0.001:(c-1)*0.001]; x=1.5*cos(2*pi*a*x0)+cos(2*pi*300*x0)+0.5*cos(2*pi*b*x0); m=nextpow2(length(x)); Nm=2^m; if length(x)<Nm x=[x,zeros(1,Nm-length(x))];%有修改 end %内置函数FFT运算结果保存到y0中 sw=fft(x); %反序 change=bin2dec(fliplr(dec2bin([1:Nm]-1,m)))+1; y=x(change); %蝶形 for sw=1:m N=2^sw;u=1; W=exp(-i*2*pi/N); for j=1:N/2 for k=j:N:Nm kp=k+N/2; g=y(kp)*u; y(kp)=y(k)-g; y(k)=y(k)+g; end u=u*W; end end save data y sw; end 加注释

好的，以下是加注释后的代码：

function y = testfft()
% 输入a、b、取样点数c
a = input('请输入f1 ');
b = input('请输入f2 ');
c = input('请输入N0 ');

% 生成信号，并进行补零操作
x0 = [0:0.001:(c-1)*0.001];
x = 1.5*cos(2*pi*a*x0) + cos(2*pi*300*x0) + 0.5*cos(2*pi*b*x0);
m = nextpow2(length(x));
Nm = 2^m;
if length(x) < Nm
    x = [x, zeros(1,Nm-length(x))]; % 补零操作
end

% 使用Matlab内置函数fft计算FFT结果
sw = fft(x); % 结果保存在变量sw中

% 对FFT结果进行反序重新排列
change = bin2dec(fliplr(dec2bin([1:Nm]-1,m))) + 1;
y = x(change);

% 进行蝶形运算
for sw = 1:m
    N = 2^sw;
    u = 1;
    W = exp(-i*2*pi/N);
    for j = 1:N/2
        for k = j:N:Nm
            kp = k + N/2;
            g = y(kp) * u;
            y(kp) = y(k) - g;
            y(k) = y(k) + g;
        end
        u = u * W;
    end
end

% 将FFT结果保存在文件data.mat中
save data y sw;
end

注释中对各个部分的解释已经写在代码后面了。不过需要注意的是，这段代码在进行FFT计算时只考虑了实部，没有考虑虚部。如果需要计算复数的FFT结果，需要使用ifft函数。

function [v1,v2,R,x1,x2,t1_,t2_,S_,flag,flag1]= get_env_feedback(v1,v2,A,x1,x2,t1,t2,S,i,episode_max,flag1) M=194.295*1000; step=0.2; v1=v1(S); v2=v2(S); f1= LineResistance(v1,M); f2= LineResistance(v2,M); flag = 0; if A ==1 %11 a1=1; F1=M*a1+f1; a2=1; F2=M*a2+f2; elseif A ==2 %12 a1=1; F1=M*a1+f1; F2=f2; a2=0; elseif A == 3 %13 a1=1; F1=M*a1+f1; F2=0; a2=-f2/M; elseif A == 4%21 a1=0; F1=f1; a2=1; F2=M*a2+f2; elseif A ==5%22 a1=0; F1=f1; F2=f2; a2=0; elseif A ==6%23 a1=0; F1=f1; F2=0; a2=-f2/M; elseif A == 7%31 F1=0; a1=-f1/M; a2=1; F2=M*a2+f2; elseif A == 8%32 F1=0; a1=-f1/M; F2=f2; a2=0; elseif A == 9%33 F1=0; a1=-f1/M; F2=0; a2=-f2/M; elseif A ==10 %41 F1=BrakingCharacteristics(v1)*1000; a1=-(F1+f1)/M; a2=1; F2=M*a2+f2; elseif A ==11 %42 F1=BrakingCharacteristics(v1)*1000; a1=-(F1+f1)/M; F2=f2; a2=0; elseif A ==12 %43 F1=BrakingCharacteristics(v1)*1000; a1=-(F1+f1)/M; F2=0; a2=-f2/M; elseif A ==13 %14 a1=1; F1=M*a1+f1; F2=BrakingCharacteristics(v2)*1000; a2=-(F2+f2)/M; elseif A ==14 %24 a1=0; F1=f1; F2=BrakingCharacteristics(v2)*1000; a2=-(F2+f2)/M; elseif A ==15 %34 F1=0; a1=-f1/M; F2=BrakingCharacteristics(v2)*1000; a2=-(F2+f2)/M; elseif A == 16 %44 F1=BrakingCharacteristics(v1)*1000; a1=-(F1+f1)/M; F2=BrakingCharacteristics(v2)*1000; a2=-(F2+f2)/M; end S_=S+1; v1(S_)=v1(S)+a1*step; v2(S_)=v2(S)+a2*step; x1(S_)=x1(S)+v1(S)*step+0.5*a1*step^2; x2(S_)=x2(S)+v2(S)*step+0.5*a2*step^2; t1_=t1+step; t2_=t2+step; v1_=v1(S_); v2_=v2(S_); x1_=x1(S_); x2_=x2(S_); if (v1_<=0 && abs(t1_-96)<=3 && abs(x1_-1530)<=10)&&(v2_<=0 && abs(t2_-96)<=3 && abs(x2_-1580)<=10) R=50; elseif x1_>1540 || v1_*3.6>=80 ||(v1_<=0 && (t1_<93||x1_<1520))||t1_>99||x2_>1590 || v2_*3.6>=80 ||(v2_<=0 && (t2_<93||x2_<1570))||t2_>99 R=-1; flag = 1; else R=0; end if flag1==1||((v1_<=0 && abs(t1_-96)<=3 && abs(x1_-1530)<=10)&&(v2_<=0 && abs(t2_-96)<=3 && abs(x2_-1580)<=10)) flag1=1; else flag1=0; end if i==episode_max figure(2) plot(x1,v1) xlabel("距离") ylabel("速度") axis([0 1531 0 22.22222222222223]) figure(3) plot(x2,v2) xlabel("距离") ylabel("速度") axis([0 1581 0 22.22222222222223]) else end end

|| v2_<=0 || x1_>1000 || x2_>1000) % Terminate episode flag1=1; % Set flag to indicate episode termination if i < episode_max % Reset environment if there are still episodes remaining v1 = [0:10:100]; % Possible values of velocity for car 1 v2 = [0:10:100]; % Possible values of velocity for car 2 x1 = zeros(length(v1),1); % Initial position of car 1 x2 = zeros(length(v2),1); % Initial position of car 2 t1_ = 0; % Initial time for car 1 t2_ = 0; % Initial time for car 2 S_ = 1; % Initial state flag = 1; % Set flag to indicate episode restart else % End of all episodes flag = -1; % Set flag to indicate end of all episodes end end R = reward_function(x1_,x2_); % Compute reward based on new positions and update the reward for the current state S = get_state(x1_,x2_,v1_,v2_); % Get the new state based on the new positions and velocitiesend