Adjustment of curve using Levenberg-Marquardt algorithm

Hi all

Thank you for my request answered in the last post. One thing I like about Labview is its ability to allow complex models to be fitted to experimental data with so much ease. I have been using the L - M unconstrained editing for some time. However, there is a question to which I thought I would like to be answered by Labview professional themselves.

When the curve adjustment is completed, the algorithm always has the minimum value for a reverse parameter. for example. Suppose that a parameter X is found to have a value of 0.8 after editing by l.-m. algorithm. However in principle several orders of values are possible for x. for example is not a sensitive parameter in the main equation so it can have values of 1000 or 400, or 60, 1. In this scenario the algorithm will always give an answer like X = 1; This is the minimum solution?

See you soon,.

Navneet

Navneet,

Implementation of Lev - Mar in LabVIEW does not explicitly attempt to diminish the importance of any parameter.  If the parameter has as little impact on the distance between the data and the best curve fit, then it will change according to the gradient of the problem.  If the parameter does not affect the distance, so that you can get a linear solver error indicating a deficiency in a row.

You can detect this behavior by using the Intervals.vi to mount curve nonlinear.  An interval that is very large compared to the other parameters would indicate a low dependence on this setting.

-Jim

Tags: NI Software

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