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Re: looking for a problem's name and possibly algorithm
From: |
Laurent Hoeltgen |
Subject: |
Re: looking for a problem's name and possibly algorithm |
Date: |
Sat, 30 Jun 2012 06:44:26 +0200 |
User-agent: |
Mozilla/5.0 (X11; Linux i686; rv:13.0) Gecko/20120615 Thunderbird/13.0.1 |
On 06/30/2012 02:03 AM, Robert Durkacz wrote:
> Is it not a Markov process?
>
> On Fri, Jun 29, 2012 at 10:58 PM, Laurent Hoeltgen <address@hidden> wrote:
>> On 06/29/2012 02:41 PM, Francesco Potortì wrote:
>>> Dear all,
>>>
>>> I have a problem which I am sure is very common, but I don't know how it
>>> is usually named.
>>>
>>> I have a system with a small number of states (N < 100), which evolves
>>> in discrete time. I have a state vector indicating the likelihood of
>>> the system to be in any of its possible states. For each time step,
>>> there can be one of a number of events (M) or no events. For each
>>> event, or the no-event situation, I have a transition matrix with which
>>> I multiply the state vector to get a new state vector.
>>>
>>> So the system evolves at each time step by multiplying the likelihood
>>> state vector by a transition matrix depending on the event happening at
>>> that time step. At each time, I declare that the system is in state S
>>> where S is the index of the state vector with the highest number.
>>>
>>> This may be made more complex by adding some memory: the currect state
>>> vector does not depend only on the immediately past one, but on a small
>>> number of past ones.
>>>
>>> What is the official name of such a model, and what are the functions
>>> that I may find useful in Octave's or Octave-forge's arsenal?
>>>
>>> Until now, I ma just doing matrix multiplication, and that looks enough,
>>> but onenever knows what's around...
>>>
>>
>> Hi,
>>
>> to me this sounds like some sort of stochastic process. You might have a
>> look at Poisson processes and similar stuff. Some people in the image
>> processing community also use quite similar models. There they are
>> sometimes referred to as diffusion or osmotic processes. For example,
>> Gaussian smoothing can be interpreted in such a way.
>>
>> Regards,
>> Laurent
>>
>> _______________________________________________
>> Help-octave mailing list
>> address@hidden
>> https://mailman.cae.wisc.edu/listinfo/help-octave
Hi
please send your answers also to the mailing list and try not to top
post (i.e put your answer below the quoted text). It makes it easier for
other people to follow the discussion.
Markov processes are a special kind of stochastic processes. The
transition matrix for a markov process only depends on the last state
and not the ones before.
Regards,
Laurent