Integral equivalent to fitting a curve to a sum of functions

AI Thread Summary
The discussion focuses on finding a mathematical transform similar to the Fourier transform that can handle an arbitrary function with a variable kernel. The user seeks a continuous equivalent for fitting a curve to a sum of functions, specifically using Gaussians, expressed through an integral involving a function F(x). They mention the Weierstrass transform as a potential solution but note its limitations regarding the variability of the standard deviation. Clarification is sought on whether the functions t(y) and f(y) are known or need to be determined. The conversation suggests that without additional information about t(y), the problem lacks sufficient data for a unique solution.
admixtus
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Hello,

I am searching for some kind of transform if it is possible, similar to a Fourier transform, but for an arbitrary function.

Sort of an inverse convolution but with a kernel that varies in each point.

Or, like I say in the title of this topic a sort of continuous equivalent of fitting a curve to a sum of functions.

For example if I want to use Gaussians, I want to reproduce a function F(x)

As:

F(x) = \int \frac{f(y)}{\sqrt{4\pi t(y)}}e^{-\frac{(x-y)^2}{4 t(y)}} dy

Notice how t is a function of y.
This is easy for a finite sum of Gaussians with linear regression, but I'm searching for a continuous equivalent.

The closest thing that I found for Gausses is a Weierstrass transform. But the 'standard deviation' of the gausses doesn't vary in each point.

There are a ton of subjects that come close (linear regression, inverse convolution, Weierstrass transform,..) but they either are discrete or lack the variability of the convoluting kernel.

Does someone know a mathematical technique that can do this? Or know in what direction I have to look? Thanks!
 
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I'm not quite clear on what is given. Obviously F is given, and you want to find f, but how about t? Is t(y) a given function?
 
haruspex said:
I'm not quite clear on what is given. Obviously F is given, and you want to find f, but how about t? Is t(y) a given function?

Yes, t(y) and f(y) are functions that I want fo find, yes. Maybe I should have written it explicitly like that instead of implying it by saying the the kernel was variable.
 
admixtus said:
Yes, t(y) and f(y) are functions that I want fo find, yes. Maybe I should have written it explicitly like that instead of implying it by saying the the kernel was variable.
From my reading of the subject (totally new to me until I saw your post) the Weierstrass transform is exactly that, a transform, so is, generally speaking, invertible. This means there is not enough information to find t. Your mission would make more sense if t(y) were given. Am I missing something?

Not sure if this is what you are after, but look at the discussion of heteroscedastic Gaussian Processes at https://www.cs.cmu.edu/~andrewgw/andrewgwthesis.pdf
 
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