On Wed, 19 Nov 2008 04:48:46 -0800, karl.polytech wrote:

> On Nov 19, 12:08 pm, karl.polyt...@googlemail.com wrote:
>> Folks,
>> It has been a while since i took my course in Probability of theory and
>> i would appreciate any help from you. I am looking to have the symbolic
>> expression of the expectation  E and Variance V of the signal Y, where:
>> Y=x1+x2 and
>> x1= cst1(a)+gaussian white noise
>> x2=cst2(a)+gaussian white noise
>> where cst1/cst2(a) returns a real value depending on the value of a
>> ["a" is a parameter uncorrelarated to the signal x1, x2, Y]
>>
>> Thank You
> 
> Guys,
> forgot to add that E(cst1)=E(Cst2), and Var(Cst1)=Var(Cst2) and both are
> known and fix

So you are saying that cst1(a) is a random variable with a variance and a 
mean, and cst2(a) is defined such that cst1(a)/cst2(a) = f(a), where f(a) 
is some unstated function of a that returns a real number?

Then without having some very interesting constraints on f(a) I don't 
think you can make your claim about the mean and variance of cst2 being 
equal to cst1, and you are supplying a woefully insufficient set of 
information for solving the problem.

Clarify, please.

-- 

Tim Wescott
Wescott Design Services
http://www.wescottdesign.com

Do you need to implement control loops in software?
"Applied Control Theory for Embedded Systems" gives you just what it says.
See details at http://www.wescottdesign.com/actfes/actfes.html

Cheers for the hints. they were so useful and sufficient to find my
way through

On Nov 19, 3:38&#4294967295;pm, "emre" <egu...@ece.neu.edu> wrote:
> >Folks,
> >It has been a while since i took my course in Probability of theory
> >and i would appreciate any help from you. I am looking to have the
> >symbolic expression of the expectation &#4294967295;E and Variance V of the signal
> >Y, where:
> >Y=x1+x2 and
> >x1= cst1(a)+gaussian white noise
> >x2=cst2(a)+gaussian white noise
> >where cst1/cst2(a) returns a real value depending on the value of a
> >["a" is a parameter uncorrelarated to the signal x1, x2, Y]
>
> >Thank You
>
> Maybe you can use these steps to get your answer:
>
> 1) Expectation is linear: &#4294967295;E[W+Z] = E[W] + E[Z].
> 2) Variance is linear if the inputs are independent: &#4294967295;V[W+Z] = V[W] +
> V[Z], given W,Z independent. (W and Z are independent if they are gaussian
> and uncorrelated, i.e. E[W Z] = E[W] E[Z].) &#4294967295;This may be the case for the
> gaussian white noise you described above, but make sure it is close to
> truth before you use that property.

>Folks,
>It has been a while since i took my course in Probability of theory
>and i would appreciate any help from you. I am looking to have the
>symbolic expression of the expectation  E and Variance V of the signal
>Y, where:
>Y=x1+x2 and
>x1= cst1(a)+gaussian white noise
>x2=cst2(a)+gaussian white noise
>where cst1/cst2(a) returns a real value depending on the value of a
>["a" is a parameter uncorrelarated to the signal x1, x2, Y]
>
>Thank You
>

Maybe you can use these steps to get your answer:

1) Expectation is linear:  E[W+Z] = E[W] + E[Z].
2) Variance is linear if the inputs are independent:  V[W+Z] = V[W] +
V[Z], given W,Z independent. (W and Z are independent if they are gaussian
and uncorrelated, i.e. E[W Z] = E[W] E[Z].)  This may be the case for the
gaussian white noise you described above, but make sure it is close to
truth before you use that property.

On Nov 19, 12:08�pm, karl.polyt...@googlemail.com wrote:
> Folks,
> It has been a while since i took my course in Probability of theory
> and i would appreciate any help from you. I am looking to have the
> symbolic expression of the expectation �E and Variance V of the signal
> Y, where:
> Y=x1+x2 and
> x1= cst1(a)+gaussian white noise
> x2=cst2(a)+gaussian white noise
> where cst1/cst2(a) returns a real value depending on the value of a
> ["a" is a parameter uncorrelarated to the signal x1, x2, Y]
>
> Thank You

Guys,
forgot to add that E(cst1)=E(Cst2), and Var(Cst1)=Var(Cst2) and both
are known and fix

Folks,
It has been a while since i took my course in Probability of theory
and i would appreciate any help from you. I am looking to have the
symbolic expression of the expectation  E and Variance V of the signal
Y, where:
Y=x1+x2 and
x1= cst1(a)+gaussian white noise
x2=cst2(a)+gaussian white noise
where cst1/cst2(a) returns a real value depending on the value of a
["a" is a parameter uncorrelarated to the signal x1, x2, Y]

Thank You