```Hi shytot,
thanks for this answer. But I will need some time to understand it.

Oliver

>>
>Its an extension of Wieners work on random signals + noise. Given a random
>signal + noise you can make an estimate of the signal. You get a smaller
>mean squared error than a Wiener filter for time-varying cases (for which
>the Wiener filter is not supposed to be applicable but is still used as part
>of an LMS algorithm or whatever).
>You will need a state-space description of your signal model.
>Can also be used for state-estimation and state-feedback control - thing
>called certainty equivalence. The optimal feedback controller for the
>noise-free case  can be used if you include a KF when there is noise.There
>are also Extended Kalman filters but they are a bit hit and miss -
>non-linear.Can be made to work but I wouldn't go near them.In such cases you
>estimate the states at the same time as the system model!
>
>Shytot
>
>

```
```Thanks, I will look for this book

>Kalman Filters are used for many things.  I suggest that you get a copy
>of "Applied Optimal Estimation" by Gelb, MIT Press.  The book is very

```
```"OZ" <oliver.zind@web.de> wrote in message
news:42db9fe3.4338312@news.btx.dtag.de...
> Hi,
> can anybody explain what Kalman filters are for ?
>
> Where can I use them ?
> What is the benefit of a Kalman filter ?
> Are there any disadvantages ?
>
> Oliver
>
Its an extension of Wieners work on random signals + noise. Given a random
signal + noise you can make an estimate of the signal. You get a smaller
mean squared error than a Wiener filter for time-varying cases (for which
the Wiener filter is not supposed to be applicable but is still used as part
of an LMS algorithm or whatever).
You will need a state-space description of your signal model.
Can also be used for state-estimation and state-feedback control - thing
called certainty equivalence. The optimal feedback controller for the
noise-free case  can be used if you include a KF when there is noise.There
are also Extended Kalman filters but they are a bit hit and miss -
non-linear.Can be made to work but I wouldn't go near them.In such cases you
estimate the states at the same time as the system model!

Shytot

```
```OZ wrote:
> Hi,
> can anybody explain what Kalman filters are for ?
>
> Where can I use them ?
> What is the benefit of a Kalman filter ?
> Are there any disadvantages ?
>
> Oliver
>

Kalman Filters are used for many things.  I suggest that you get a copy
of "Applied Optimal Estimation" by Gelb, MIT Press.  The book is very
```
```OZ wrote:
> Hi,
> can anybody explain what Kalman filters are for ?
>
> Where can I use them ?
> What is the benefit of a Kalman filter ?
> Are there any disadvantages ?

Jerry
--
Engineering is the art of making what you want from things you can get.
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```
```Hi,