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Description: We can use least squares to solve general linear equations, and we can use LM to solve general nonlinear equations.
Here is a system of linear differential equations, so we use least squares to solve.
The key is to construct the least squares form, the differential can be obtained by the method of difference between the front and back data.
However, there is another trick here. If the data is too long before and after the frame interval, you can first interpolate, and then the data difference after interpolation. If the actual measured data jitter is too large, the difference after interpolation obviously can not reflect the actual situation, you can smooth the data first Sum or average) and then find the difference.
(Click to check if it's the file you need, and recomment it at the bottom):
|main.txt|| 1815 || 2021-02-20
|SEIR.txt|| 304 || 2021-02-20|