how to implement following equation with limits in labview

[rashi]

kindly send me VI made by you in 2010 version so that i can open it

[aSquared1]

Hi rashi,

The VI is not really an example, it was a trial that I made in order to understand your question.

Still, my understanding with this iterative coefficients filtering is a bit fuzzy.

I am not familiar with the LMS algorithm.

I am adding the trial VI that I made when you asked "how to apply limits and how to give two conditions".

in version 2010 this time (it could be efficient to add your LV to your signature).

Now to the problem itself:

"You can implement an LMS adaptive filter using the LabVIEW Adaptive Filter Toolkit. You also can implement an LMS adaptive filter using the LabVIEW graphical development environment without the Adaptive Filter Toolkit. Typically, there are two types of application programming interface (API) designs for an adaptive filter."

this quote is taken from here - http://zone.ni.com/devzone/cda/epd/p/id/6220

and shows examples of the block diagram

if you are interested in the LabVIEW Adaptive Filter Toolkit, you can read more here -

http://sine.ni.com/nips/cds/view/p/lang/en/nid/209039

Since you are using LabVIEW 2010, if the download version on the web is not compatible, I can upload a version that is compatible to the FTP if you wish. in each way, you will be able to evaluate it for 30 days.

Now, Lets try to investigate your try to implement an LMS adaptive filter using the LabVIEW graphical development environment without the Adaptive Filter Toolkit.

I am Trying to understand what Vectors and Parameters are given and what aren't.

Lets try to make a list. correct me where I am wrong.

u1 - small step size - given

u2 - large step size - given

T - Length of comparison interval. - given.

L - Number of comparisons. - given

x(n) - input array - given

e1(n) - output error array of the speed filter - given ??

e2(n) - output error array of the accuracy filter- given ??

Q(n) - defined using e1(n) and e2(n) so can be calculated when e1(n) and e2(n) are given

w(n) - output noise array - given ?

y(n) - ????

y2(n) - ????

and for summing it all:

h2(n+1) - vector of the speed filter coefficients , calculated point by point so we need to know h2(0)

                 we also need to know e2(n)

h1(n+1) - vector of the accuracy filter coefficients , calculated point by point so we need to know h1(0)

                 we also need to know e1(n), in some conditions we need to know e2(n) too.

so... if e2(n) and e1(n) are known inputs of the VI and also we know h1(0) and h2(0) , I can make you a simple example that iterates to calculate the  filter coefficients array.

Something extra :

Here is a link to NI.com after searching for 'LMS' and choosing to see only the Examples.

http://search.ni.com/nisearch/app/main/p/bot/no/ap/tech/lang/en/pg/1/sn/catnav:ex/q/lms/scope/en%2Ch...

A more specific link -

Play Demo and Learn Signal Processing - LMS Adaptive Filter

https://decibel.ni.com/content/docs/DOC-5054