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Author Topic: The "Suspension of Fuckwittery" Challenge Thread - Q&A Sessions - 2007  (Read 3935 times)

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Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 

Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
Well, i have no idea what you mean by similar fashion to Bayesian stats used in GPS.
The Kalman filter is as highly dependant on the initial estimate as of the state variables.
Given poor level of initial conditions or information, it does not matter how efficient your filter is you are not going to get any convergence. ie. decent predicition, without the initial predictor being within a certain boundary.
If this is the case, then the Kalman filter is only really measuring parameters rather than predicting, and once these parameters are estimated within what you called a level of accuracy, then we are back to how good your initial prediction is, in deciding how effective the filter is.
This is my initial question.
ie. Why bother with the filter, and just concentrate on the estimator ?


I assume the filter helps the estimator stage, maybe the algorithms cannot be applied directly.
I have no idea what you mean.

Offline Christopher McCandless

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What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.

Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?

Offline Christopher McCandless

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  • "I HAVE HAD A HAPPY LIFE AND THANK THE LORD. GOODB
    • Into the Wild
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.

Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


Offline Christopher McCandless

  • Wild Wanderer of the Aspie Elite
  • Elder
  • Insane Postwhore
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  • Posts: 10626
  • Karma: 132
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  • "I HAVE HAD A HAPPY LIFE AND THANK THE LORD. GOODB
    • Into the Wild
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?

Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?
:laugh:
Well:
1. It's wikipedia. Obviously it has some basis, but i wouldn't regard it as gospell.
2. You would be surprised about the needless shit in some military applications.

Offline Christopher McCandless

  • Wild Wanderer of the Aspie Elite
  • Elder
  • Insane Postwhore
  • *****
  • Posts: 10626
  • Karma: 132
  • Gender: Male
  • "I HAVE HAD A HAPPY LIFE AND THANK THE LORD. GOODB
    • Into the Wild
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?
:laugh:
Well:
1. It's wikipedia. Obviously it has some basis, but i wouldn't regard it as gospell.
2. You would be surprised about the needless shit in some military applications.
No they want you to think its needless, maybe it has a function, or the filter doesnt exist at all and its a code for something else...

Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?
:laugh:
Well:
1. It's wikipedia. Obviously it has some basis, but i wouldn't regard it as gospell.
2. You would be surprised about the needless shit in some military applications.
No they want you to think its needless, maybe it has a function, or the filter doesnt exist at all and its a code for something else...
Well whatever, they used to pay me for the needless shit. That's all i bothered about.

Offline Christopher McCandless

  • Wild Wanderer of the Aspie Elite
  • Elder
  • Insane Postwhore
  • *****
  • Posts: 10626
  • Karma: 132
  • Gender: Male
  • "I HAVE HAD A HAPPY LIFE AND THANK THE LORD. GOODB
    • Into the Wild
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?
:laugh:
Well:
1. It's wikipedia. Obviously it has some basis, but i wouldn't regard it as gospell.
2. You would be surprised about the needless shit in some military applications.
No they want you to think its needless, maybe it has a function, or the filter doesnt exist at all and its a code for something else...
Well whatever, they used to pay me for the needless shit. That's all i bothered about.
Lol, they probably knew it was needless, or you wernt working for the top level millatary. They replaced your needless stuff with something else, or adapted it...

Kosmonaut

  • Guest
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?
:laugh:
Well:
1. It's wikipedia. Obviously it has some basis, but i wouldn't regard it as gospell.
2. You would be surprised about the needless shit in some military applications.
No they want you to think its needless, maybe it has a function, or the filter doesnt exist at all and its a code for something else...
Well whatever, they used to pay me for the needless shit. That's all i bothered about.
Lol, they probably knew it was needless, or you wernt working for the top level millatary. They replaced your needless stuff with something else, or adapted it...
that, or used the alien technology.

Offline Christopher McCandless

  • Wild Wanderer of the Aspie Elite
  • Elder
  • Insane Postwhore
  • *****
  • Posts: 10626
  • Karma: 132
  • Gender: Male
  • "I HAVE HAD A HAPPY LIFE AND THANK THE LORD. GOODB
    • Into the Wild
What is the point in a Kalman filter ? Why don't people just come up with a decent estimator in the first place and cut out all the bullshit ?
Lack of computational power or lack of information. In both cases you can only approximate. Look at this. http://en.wikipedia.org/wiki/Kalman_filter
I am aware of wikipedia.
I refer you to the original question. You may assume infinite computational power.
Ok, then the second premise where not all the information is not there, or not to a level of accuracy. A simple example is the Radar, there is always interference with the signal. The filter approximates to find and enemy location, in a similar fashion to the Bayesian stats used in GPS.
i bet it is a very long time before you get laid.
I doubt it McJ, I can get laid when I want to, I have pretty high levels of personal charisma. Bear in mind maths is my specialism really, so I do know the stuff...
I doubt that either personal charisma or maths is your speciality.
Do you see why ?
 
Maths, I have 2 alevels in it both A's hopefully and am off to take it to degree level probably along with other things. Also I do read quite heavily around the subject.
As for personal charisma, you would be surprised what I have talked to people into over the years, and people do admire and respect me (good ears help in finding out about that one).
The estimations are a process carried out by an approximation algortihm. The filters are needed to clear it up before the algorithm is applied.
Well, that's great news.
I doubt you will do this in a mathematics degree though ( unless you are unlucky, or a big enough idiot to actually choose to).
Anyway, you don't need a 'filter' to 'clear it up' if you have a decent approximation in the first place given the parameters. If the parameters are not accurate due to incomplete information, then all your 'filter' is doing is gaining more information. Which you could just measure anyway.
The state variables are just measurements to calculate parameters for the predictor.
If state variables are accurate then the Kalman filter converges with respect to how good your initial estimator is.
Hence, my question.
Why not put the effort into getting a good predictor, instead of all the bullshit ?
Simple the system works. What would be a new application of your improved system?
As for the maths degree, I am doing Nat Sci with maths modules in it and also CS modules so far, but i can change my mind.
Not without a decent estimator it doesnt, which is my point.


It seems to work well in the applications given in the wikipedia article... Maybe the estimator and the filter work better together, they wouldnt fit it needlessly in a millatary application would they?
:laugh:
Well:
1. It's wikipedia. Obviously it has some basis, but i wouldn't regard it as gospell.
2. You would be surprised about the needless shit in some military applications.
No they want you to think its needless, maybe it has a function, or the filter doesnt exist at all and its a code for something else...
Well whatever, they used to pay me for the needless shit. That's all i bothered about.
Lol, they probably knew it was needless, or you wernt working for the top level millatary. They replaced your needless stuff with something else, or adapted it...
that, or used the alien technology.
lol, the alien technology sounds fun...

Offline z.twelve

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What's the point?  www.google.com

Ed, you are being myopic. Any pea-brained individual can use google. The point is to generate interesting and diverse Q&A within the confines of this thread. It is about sharing ideas between unique individuals that would not otherwise have been thought of by another.

Hooray, someone gets it:

What is the exact dimension of the universe ?

The exact dimension of the universe is only constant for an infinitely short amount of time. Therefore ignoring the fact that it is so vast that the size cannot be measured accurately, it's expansion would render any specific accurate measurement only valid for one particular, infinitely short amount of time. Current scientific estimates place it's volume at somewhere between, "extremely fucking huge" and "abso-fucking-lutely gargantuan".



At what age did you first realise you were born without imagination? Oh wait... don't answer that.

To the guys contributing positively, good stuff :asthing:


Offline McGiver

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