# Nonlinear Regression Curve Fitting

This isn't a precise homework question, but this seemed like the most reasonable place to post. If not, please feel free to move it.

I have a large set of data points that should fit to a known equation (the Drude-Smith model for conductivity)

The equation the data should fit to is: σ(ω) = (ε0ωp2τ)/(1-iωτ) * [1+Σ(cn)/(1-iωτ)].

I have all of the data, so I have hundreds of data points for σ(ω). I need to have values for other fitting parameters, namely ωp, cn, and τ. To make it solvable, I figure I can do some algebra on the above equation to split it into real and imaginary components, then let ωp be constant. Then, I technically have 2 "equations" (1 real 1 imaginary)and 2 "unknowns" (cn and τ). However, I am unsure how to fit this. Any help would be appreciated.

Note: I will be using MATLAB.

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Student100
Gold Member
This isn't a precise homework question, but this seemed like the most reasonable place to post. If not, please feel free to move it.

I have a large set of data points that should fit to a known equation (the Drude-Smith model for conductivity)

The equation the data should fit to is: σ(ω) = (ε0ωp2τ)/(1-iωτ) * [1+Σ(cn)/(1-iωτ)].

I have all of the data, so I have hundreds of data points for σ(ω). I need to have values for other fitting parameters, namely ωp, cn, and τ. To make it solvable, I figure I can do some algebra on the above equation to split it into real and imaginary components, then let ωp be constant. Then, I technically have 2 "equations" (1 real 1 imaginary)and 2 "unknowns" (cn and τ). However, I am unsure how to fit this. Any help would be appreciated.

Note: I will be using MATLAB.