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Error propagation with two functions, two unknowns. |
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| Aug6-12, 04:48 PM | #1 |
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Error propagation with two functions, two unknowns.
If I have two independent variables x,y, and two measurements, m1, m2 with errors. And the dependence is thus:
[tex] m_1 \pm \delta m_1 = f[x,y] [/tex] [tex] m_2 \pm \delta m_2 = g[x,y] [/tex] Now in my case, f and g are complicated expressions of x and y with no simple solution. (Actually I think i can solve one for x, but not for y). Now if the equations were easy, I could solve for x and y: [tex] x \pm \delta_x = F[m_1, m_2,...] [/tex] [tex] y \pm \delta_y = G[m_1, m_2,...] [/tex] And from there add the errors in quadrature to get the x and y errors. BUT if I cant solve for x and y independently, and I must use numerical solutions to get the results ( I can, its easy). How can I go about getting the ERRORS? Is there another way I can solve for the errors and numerically solve for them, or a different method? I have Mathematica if that helps. |
| Aug7-12, 10:01 PM | #2 |
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Recognitions:
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You should explain what you mean by "error". Are you doing numerical approximations that involve an error in that sense? Are you doing a stochastic simulation where randomness causes an "error"? Or are you teking physical measurements with equipment that has a specified precision?
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| Aug8-12, 12:58 AM | #3 |
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Recognitions:
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Are f, g differentiable? Can you evaluate the derivatives at (m1, m2)? If so, can write [tex]\delta m_1 = \delta f = f_x \delta x + f_y \delta y; \delta m_2 = \delta g = g_x \delta x + g_y \delta y[/tex] Evaluating fx etc. at (m1, m2), solve to find δx, δy. Will need to check that the second order terms are not important. |
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