필터 지우기
필터 지우기

How to plot this signal?

조회 수: 2 (최근 30일)
Negar
Negar 2011년 2월 20일
Hi everyone, Can anybody tell me how to define this function and plot it in Matlab?
X(n) = X(n-1)+ 0.9 e(n)
where e(n) is a white,gaussian noise signal, and X(n) is a stationary, gaussian AR(1) process
  댓글 수: 1
Negar
Negar 2011년 2월 20일
Sorry Zohar but can you explain to me what you mean by 'not using first element' ? And why did you start n from 2 , and not from 1 ? I am not good at MATLAB at all ...

댓글을 달려면 로그인하십시오.

채택된 답변

zohar
zohar 2011년 2월 20일
Hi Negar
l = 1000;% length of the signal
x = zeros(l,1);
Noise = 0.9*randn(l,1); % not using first element
% not using first element
% assuming x(0) = 0 or somthing else
for n = 2: length(x)
x(n) = x(n-1)+ Noise(n);
end
% or you can use
x (2:length(x)) = x (1:length(x)-1) + Noise(2:length(x));
plot(1:l,x)
I hope it's help you.

추가 답변 (6개)

Negar
Negar 2011년 2월 20일
Thank U a lot Zohar, I'll try it..

Negar
Negar 2011년 2월 20일
Sorry but can you explain to me what you mean by 'not using first element' ? And why did you start n from 2 , and not from 1 ? I am not good at MATLAB at all ...

zohar
zohar 2011년 2월 20일
Hi Negar
l = 1000;% length of the signal
x = zeros(l,1);
Noise = 0.9*randn(l,1);
% sorry I meant the first element of x, x(1) not x(0)
%assuming x(1) = 0 or somthing else
for n = 2: length(x)
x(n) = x(n-1)+ Noise(n);
end
% or you can use
x (2:length(x)) = x(1:length(x)-1) + Noise(2:length(x));
plot(1:l,x)
I start with n=2 because x(1) allready defined 0.

Negar
Negar 2011년 2월 20일
Thank you so much Zohar , it really helped :)))))
Now , I have another question, how to find power spectral density of x(n)? I have made this code:
clc close all clear all
ro=0.9; % The nearest sample correlation l = 1000;% Length of the input signal x(n) x = zeros(l,1); E = randn(l,1); % Gaussian ,white noise signal e(n)
for n = 2: length(x) % Generation of the input signal x(n) = ro*x(n-1)+ sqrt(1-ro^2)*E(n);
end y =xcorr(x,x); % Autocorrelation function for x(n) plot(y); title('Autocorrelation function of input signal');
figure psd_x= psd(x); plot(psd_x); % power spectral density of signal x(n)
Is this a correct way to fin autocorrelation function and psd?
  댓글 수: 1
zohar
zohar 2011년 2월 21일
It's looks ok type help psd to figure out more about spectrum.psd.

댓글을 달려면 로그인하십시오.


Negar
Negar 2011년 2월 20일
ufffff by the way how did you type your code? I couldn't change the font like yours...

Negar
Negar 2011년 2월 20일
ok I think I found the answer, in order to fin psd, I should take FT of the autocorrelation function... I hope you will correct me if I am not right :)

카테고리

Help CenterFile Exchange에서 Parametric Spectral Estimation에 대해 자세히 알아보기

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by