nikelodeon: Whatever... Chebyshev, Hrenebyshev. What's next???? What's the financial point then?
Well firstly, only because Chebyshev is a scientist who made many discoveries in mathematics, I think it's silly to call him"Khrenebyshev".And secondly, I'm trying to find a better version of the muwings and that's all.
I tried all these fatl-satl, jma-jjma, supersmoother and various spectral analysis sketches
I finally understood that it was an attempt to find an "ideal" smoothed line but there would still be false reversals/crossings, so I decided to give up
Guys, adaptivity is an ability, a property of dynamic optimization of parameters of a Controlled Dynamic System (yes yes - don't laugh).
It is achieved by including in the main algorithm a module that simulates this algorithm (its efficiency) and an optimization block that uses this module.
Implementation is not particularly difficult, if you understand thoroughly what your algorithm does and why. The main problem is high computational complexity, which can easily be reduced by 2-4 times.
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And what is adaptability anyway?
It's when there's a flood and your gills suddenly form )))
And what is adaptability anyway?
Whatever... Chebyshev, Hrenebyshev. What's next???? What's the financial point then?
I have tried different filters of this kind and found that they have little or no advantage over standard muwings
Can I ask what "different" means?
I tried all these fatl-satl, jma-jjma, supersmoother and various spectral analysis sketches
I finally understood that it was an attempt to find an "ideal" smoothed line but there would still be false reversals/crossings, so I decided to give up
I tried all these fatl-satl, jma-jjma, supersmoother and various spectral analysis sketches
eventually realized it was an attempt to find the "ideal" smoothed line but there would still be false reversals/crossings and decided to give up
Guys, adaptivity is an ability, a property of dynamic optimization of parameters of a Controlled Dynamic System (yes yes - don't laugh).
It is achieved by including in the main algorithm a module that simulates this algorithm (its efficiency) and an optimization block that uses this module.
Implementation is not particularly difficult, if you understand thoroughly what your algorithm does and why. The main problem is high computational complexity, which can easily be reduced by 2-4 times.