Nonlinear least squares problem

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A nonlinear least squares fitting problem is presented involving parametric equations where constants a, b, c, x0, y0, and z0 need to be determined from pixel data (u', v'). The discussion highlights the necessity of deriving a single nonparametric function from the parametric equations to perform the fitting, but the user encounters difficulties in solving for the variable t. Questions arise regarding the feasibility of obtaining a nonparametric equation from the given parametric forms and whether a nonlinear least squares fit is possible. It is noted that the approach to least squares fitting may be misunderstood, as it typically involves fitting a function to data rather than deriving data from a function. The conversation emphasizes the challenges and considerations in applying nonlinear least squares to parametric equations.
ciaran_hughes
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Dear all,

Apologies if this is in the wrong forum.

I have a bit Nonlinear least squares fit problem. I have a pair of parametric equations (see attached, fairly nasty :frown: ).

in it, a b c x0 y0 z0 are all constant, and they are the values I want to determine from a nonlinear least squares fit to a given set of (u', v') data. (u', v') are a set of pixel locations of a curve in an image, and the equations attached describe that curve.

Now, to do a nonlinear least squares, I believe I have to get a single nonparametric function (e.g. of v' in terms of u'). To do this, I follow the standard steps of solving one of the equations in terms of t, and substitute into the other. This is where I fail.

I have even used the 'solve' function in the Symbolic Toolbox in MATLAB to solve one of the equations for t, but simply get an error.

So, my questions are:
1) Am I right in saying I must get the non-parametric equation for the curve to get a nonlinear least squares fit to the data points? I assume that I do, because t is an extra variable that I a) don't need and b) have no information for.
2) Can a nonparametric equation for this curve be obtained (from the attached equations)? Why?

Ultimately, I would like to know if I can do a nonlinear least squares fit to these parametric equations. If I can't, or if it would prove very difficult, why?

Many thanks for your time,
Ciaran
 

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A least squares fit produces a function based on a collection of data.

If you have the function and want to produce data, it is called evaluation.

So you're thinking about least squares backward.
 
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