优化以下代码 function [At,Ph,A2]=EnvelopPhase(X,f0,fs) HX=imag(hilbert(X)); [M,N]=size(X); t=0:1/fs:((N-1)/fs); Ac=X.cos(2pif0t)+HX.sin(2pif0t); As=HX.cos(2pif0t)-X.sin(2pif0t); Ph=atan(As./Ac); A2=Ac.*Ac+As.*As; At=sqrt(A2); function X=Narrowbandsignal(N,f0,delt,fs,M); N1=N-M; xt=random(‘norm’,0,1,[1,N1]); f1=f0*2/fs; df=delt/fs; ht=fir1(M,[f1-df f1+df]); X=conv(xt,ht) return N=10000;f0=10000;delt=400;fs=22000;M=50; al=2;a2=4;a3=8; sitl=pi/6;sit2=pi/4;sit3=pi/3 X=Narrowbandsignal(N,f0,delt,fs,M); X=X/sqrt(var(X)); t=0:1/fs:((N-1)/fs); X1=X+alcos(2pif0t+sitl); X2=X+a2cos(2pif0t+sit2); X3=X+a3cos(2pif0t+sit3); [Atl,Ph1,A21]=EnvelopPhase(X1, f0, fs); [At2,Ph2,A22]=EnvelopPhase(X2, f0, fs); [At3,Ph3,A23]=EnvelopPhase(X3, f0, fs); LA=0:0.4:12; GA1=hist(Atl, LA); GA2=hist(At2, LA); GA3=hist(At3, LA); plot(LA,GA1,‘:’,LA,GA2,‘-’,LA,GA3,‘–’); title(“包络的分布直方图”); figure; LP=-pi/2:0.05:pi/2; GP1=hist((Ph1-sitl),LP); GP2=hist((Ph2-sit2),LP); GP3=hist((Ph3-sit3),LP); plot(LP,GP1,‘:’,LP,GP2,‘-’,LP,GP3,‘–’); title(“相位的分布直方图”); figure; LA2=0:1:120; GA21=hist(A21,LA2); GA22=hist(A22,LA2); GA23=hist(A23,LA2); plot(LA2,GA21,‘:’, LA2,GA22,‘-’,LA2,GA23,‘–’); title(‘包络平方值的分布直方图’);

以下是优化后的代码：

function [At,Ph,A2]=EnvelopPhase(X,f0,fs)
HX=imag(hilbert(X));
t=0:1/fs:((length(X)-1)/fs);
Ac=X.*cos(2*pi*f0*t)+HX.*sin(2*pi*f0*t);
As=HX.*cos(2*pi*f0*t)-X.*sin(2*pi*f0*t);
Ph=atan2(As,Ac);
A2=Ac.^2+As.^2;
At=sqrt(A2);
end

function X=Narrowbandsignal(N,f0,delt,fs,M)
N1=N-M;
xt=randn(1,N1);
f1=f0*2/fs;
df=delt/fs;
ht=fir1(M,[f1-df f1+df]);
X=conv(xt,ht);
X=X(1:N);
end

N=10000;
f0=10000;
delt=400;
fs=22000;
M=50;
al=2;
a2=4;
a3=8;
sitl=pi/6;
sit2=pi/4;
sit3=pi/3;

X=Narrowbandsignal(N,f0,delt,fs,M);
X=X/sqrt(var(X));

t=0:1/fs:((N-1)/fs);

X1=X+al*cos(2*pi*f0*t+sitl);
X2=X+a2*cos(2*pi*f0*t+sit2);
X3=X+a3*cos(2*pi*f0*t+sit3);

[Atl,Ph1,A21]=EnvelopPhase(X1, f0, fs);
[At2,Ph2,A22]=EnvelopPhase(X2, f0, fs);
[At3,Ph3,A23]=EnvelopPhase(X3, f0, fs);

LA=0:0.4:12;
GA1=histcounts(Atl, LA);
GA2=histcounts(At2, LA);
GA3=histcounts(At3, LA);
figure;
plot(LA,GA1,':',LA,GA2,'-',LA,GA3,'--');
title('包络的分布直方图');

LP=-pi/2:0.05:pi/2;
GP1=histcounts((Ph1-sitl),LP);
GP2=histcounts((Ph2-sit2),LP);
GP3=histcounts((Ph3-sit3),LP);
figure;
plot(LP,GP1,':',LP,GP2,'-',LP,GP3,'--');
title('相位的分布直方图');

LA2=0:1:120;
GA21=histcounts(A21,LA2);
GA22=histcounts(A22,LA2);
GA23=histcounts(A23,LA2);
figure;
plot(LA2,GA21,':', LA2,GA22,'-',LA2,GA23,'--');
title('包络平方值的分布直方图');

主要的优化包括：

1. 使用点乘（.*）和平方（.^2）代替矩阵乘法和幂运算，这样可以提高代码的执行效率。

2. 使用 atan2() 函数代替 atan() 函数，这样可以避免计算出现奇点的情况。

3. 使用 histcounts() 函数代替 hist() 函数，这样可以更方便地进行直方图统计。