求標(biāo)準(zhǔn)偏差
> function c=myfunction(x)
> [m,n]=size(x)
> t=0
> for i=1:numel(x)
> t=t+x(i)*x(i)
> end
> c=sqrt(t/(m*n-1))
function c=myfunction(x)
[m,n]=size(x)
t=0
for i=1:m
for j=1:n
t=t+x(i,j)*x(i,j)
end
end
c=sqrt(t/(m*n-1
求標(biāo)準(zhǔn)偏差
> function c=myfunction(x)
> [m,n]=size(x)
> t=0
> for i=1:numel(x)
> t=t+x(i)*x(i)
> end
> c=sqrt(t/(m*n-1))
function c=myfunction(x)
[m,n]=size(x)
t=0
for i=1:m
for j=1:n
t=t+x(i,j)*x(i,j)
end
end
c=sqrt(t/(m*n-1
求標(biāo)準(zhǔn)偏差
> function c=myfunction(x)
> [m,n]=size(x)
> t=0
> for i=1:numel(x)
> t=t+x(i)*x(i)
> end
> c=sqrt(t/(m*n-1))
function c=myfunction(x)
[m,n]=size(x)
t=0
for i=1:m
for j=1:n
t=t+x(i,j)*x(i,j)
end
end
c=sqrt(t/(m*n-1
求標(biāo)準(zhǔn)偏差
> function c=myfunction(x)
> [m,n]=size(x)
> t=0
> for i=1:numel(x)
> t=t+x(i)*x(i)
> end
> c=sqrt(t/(m*n-1))
function c=myfunction(x)
[m,n]=size(x)
t=0
for i=1:m
for j=1:n
t=t+x(i,j)*x(i,j)
end
end
c=sqrt(t/(m*n-1
The Window Design Method
The basic idea behind the design of linear-phase FIR filters using the window
method is to choose a proper ideal frequency-selective filter [which always has
a noncausal, infinite duration impulse response] and then truncate its impulse
response hd[n] to obtain a linear-phase and causal FIR filter h[n]. To truncate the
impulse response of the ideal filter a time window w[n] is used. Available windows
in Matlab are rectangular [or boxcar in Matlab], bartlett, hamming, hanning
