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Thread Subject:
correlated noise

Subject: correlated noise

From: julie

Date: 15 Nov, 2005 09:48:45

Message: 1 of 6

i need matlab code to generate correlated noise from random noise

Subject: correlated noise

From: John D'Errico

Date: 15 Nov, 2005 16:09:25

Message: 2 of 6

In article <ef1b781.-1@webx.raydaftYaTP>,
 julie <julie.iskander@gmail.com> wrote:

> i need matlab code to generate correlated noise from random noise

Since you say absolutely nothing about distribution,
there is little to directly suggest. Be more
explicit with your questions and you will get better
help.

In general, you can use some of the tools in the
statistics toolbox to do this. It can be done using
the functions filter or conv, or even linear algebra.

That will cover at least a few of the possible
solutions for a question this broad.

HTH,
John D'Errico


--
The best material model of a cat is another, or preferably the same, cat.
A. Rosenblueth, Philosophy of Science, 1945

Those who can't laugh at themselves leave the job to others.
Anonymous

Subject: correlated noise

From: John

Date: 15 Nov, 2005 19:05:54

Message: 3 of 6

x=randn(1,1000)
[b,a]=butter(2,0.4);
y=filter(b,a,x)

y is non-white noise

__________
"julie" <julie.iskander@gmail.com> skrev i en meddelelse
news:ef1b781.-1@webx.raydaftYaTP...
>i need matlab code to generate correlated noise from random noise

Subject: correlated noise

From: julie

Date: 20 Nov, 2005 03:09:48

Message: 4 of 6

I need to generate correlated noise with a certain covariance matrix
c=[ 1 0.8 0.3
    0.8 1 0.8
    0.3 0.8 1]

Subject: correlated noise

From: ellieandrogerxyzzy@mindspring.com.invalid (Roger Stafford)

Date: 20 Nov, 2005 15:22:44

Message: 5 of 6

In article <ef1b781.2@webx.raydaftYaTP>, Julie <julie.iskander@gmail.com> wrote:

> I need to generate correlated noise with a certain covariance matrix
> c=[ 1 0.8 0.3
> 0.8 1 0.8
> 0.3 0.8 1]
-----------------------
  Just specifying the covariance of three random variables doesn't
determine their probability distribution. Many different joint
distributions can have the same covariance.

  However, if you want a joint normal distribution with given mean value,
then you need to use the Statistics Toolbox function 'mvnrnd'. Either
that, or take appropriate linear combinations of three independent
variables generated by 'randn'. For example,

[V,D] = eig(c);
X = (V*sqrt(D))*randn(3,n);
x1 = X(1,:); x2 = X(2,:); x3 = X(3,:);

will generate random variables x1, x2, x3 as n-element row vectors which
statistically have a joint normal distribution with mean 0 and covariance
c. For large n their actual distribution should approach this theoretical
one.

(Remove "xyzzy" and ".invalid" to send me email.)
Roger Stafford

Subject: correlated noise

From: Angelia

Date: 30 Mar, 2013 19:25:13

Message: 6 of 6

Why does using a low pass filter create correlated noise?

"John" <johnjohn@sucker.com> wrote in message <437a238d$0$78282$157c6196@dreader1.cybercity.dk>...
> x=randn(1,1000)
> [b,a]=butter(2,0.4);
> y=filter(b,a,x)
>
> y is non-white noise
>
> __________
> "julie" <julie.iskander@gmail.com> skrev i en meddelelse
> news:ef1b781.-1@webx.raydaftYaTP...
> >i need matlab code to generate correlated noise from random noise
>
>

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