Finding Optimal Parameters for Complex Function f(x)

In summary, you are trying to find the best values for a,b,c of the complex function f(x)=a+\frac{b-a}{1+j x c} of the real variable x where (j^2=-1). This is a curve fitting problem, but the function f(x) is complex. You can try to find a minimum value of the square of the error S between the actual value of the function f(x) and the desired value by solving for (a,b,c) in a system of three equations.
  • #1
kprokopi
2
0
hi,
I face the following problem.
I need to find the best values of the parameters [itex]a,b,c[/itex]
of the complex function [itex]f(x)=a+\frac{b-a}{1+j x c}[/itex] of the real
variable [itex]x[/itex] where ([itex]j^2=-1[/itex])
such that
[itex]f(2 \pi 10^6)=2.33-j 1.165 10^{-3}[/itex] and
[itex]f(2 \pi 10^{10})=2.347-j 3.7552 10^{-3}[/itex].

It seems to be a curve fitting problem but the function [itex]f(x)[/itex] is complex!
 
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  • #2
True enough; you have three constants to optimize to 4 restraints.
What's your problem?
 
  • #3
Oh, those engineers and their jmaginary numbers!
 
  • #4
To get you started:
1. Define:
[tex]x_{0}=2\pi{10}^{6}[/tex]
[tex]x_{1}=2\pi{10}^{10}[/tex]
Ask yourself:
Why have you been given so huge arguments?
In particular, can I use that fact to my advantage later on?

2.Rewrite:
[tex]f(x)=a+\frac{b-a}{1+jxc}=a+\frac{1-jxc}{1-jxc}\frac{b-a}{1+jxc}=\frac{ax^{2}c^{2}+b}{1+x^{2}c^{2}}+j\frac{(a-b)xc}{1+x^{2}c^{2}}[/tex]
3. Requirements of curve fitting:
[tex]\frac{ax_{0}^{2}c^{2}+b}{1+x_{0}^{2}c^{2}}\approx{2.33}[/tex]
[tex]\frac{ax_{1}^{2}c^{2}+b}{1+x_{1}^{2}c^{2}}\approx{2.347}[/tex]
[tex]\frac{(a-b)x_{0}c}{1+x_{0}^{2}c^{2}}\approx{-1.16510*10^{-3}}[/tex]
[tex]\frac{(a-b)x_{1}c}{1+x_{1}^{2}c^{2}}\approx{-3.755210*10^{-3}}[/tex]
4. Define:
[tex]y_{0r}=2.33,y_{1r}=2.347,y_{0i}=-1.16510*10^{-3},y_{1i}=-3.755210*10^{-3}[/tex]
5. Define:
[tex]\hat{y}_{0r}=\frac{ax_{0}^{2}c^{2}+b}{1+x_{0}^{2}c^{2}}[/tex]
[tex]\hat{y}_{1r}=\frac{ax_{1}^{2}c^{2}+b}{1+x_{1}^{2}c^{2}}[/tex]
[tex]\hat{y}_{0i}=\frac{(a-b)x_{0}c}{1+x_{0}^{2}c^{2}}[/tex]
[tex]\hat{y}_{1i}=\frac{(a-b)x_{1}c}{1+x_{1}^{2}c^{2}}[/tex]

6. Construct:
[tex]S(a,b,c)=(y_{0r}-\hat{y}_{0r})^{2}+(y_{0i}-\hat{y}_{0i})^{2}+(y_{1r}-\hat{y}_{1r})^{2}+(y_{1i}-\hat{y}_{1i})^{2}[/tex]

Clearly, S>=0, and S=0 if and only if the curve fitting is exact.
We are interested in the choice of (a,b,c) such that a minimum of S is found.
Hence, we should consider the system of 3 equations:
[tex]\frac{\partial{S}}{\partial{a}}=0[/tex]
[tex]\frac{\partial{S}}{\partial{b}}=0[/tex]
[tex]\frac{\partial{S}}{\partial{c}}=0[/tex]

This system can (theoretically, at least!) be solved for minimizing values
[tex](a_{m},b_{m},c_{m})[/tex]
To find a simple, approximate solution to the system of equations, I suggest that you utilize your knowledge that [tex](x_{0},x_{1})[/tex] are huge numbers.
Good luck!
NOTE:
This is just one of many techniques to derive curve-fitting coefficients.
It is by no means clear that this technique provides the simplest system to solve for coefficients (a,b,c). Look up in a numerical analysis book (or something like that) to get other ideas..
 
Last edited:
  • #5
HallsofIvy said:
Oh, those engineers and their jmaginary numbers!


Hahaha :rofl:
 

1. What is the purpose of finding optimal parameters for a complex function?

The goal of finding optimal parameters for a complex function is to determine the values of the inputs that will result in the best possible output. This is important for various applications in science and engineering, where the function represents a real-world system or phenomenon.

2. How do you determine the optimal parameters for a complex function?

There are various methods for finding optimal parameters, including trial and error, gradient descent, and genetic algorithms. These methods involve systematically adjusting the input values and evaluating the resulting output until the best combination of parameters is found.

3. What factors influence the optimal parameters for a complex function?

The optimal parameters for a complex function can be influenced by a variety of factors, including the structure of the function, the range of possible input values, and the desired output. The complexity of the function and the availability of data can also play a role in determining the optimal parameters.

4. Can the optimal parameters for a complex function change over time?

Yes, the optimal parameters for a complex function can change over time due to changes in the underlying system or new data becoming available. It is important to regularly reassess and update the optimal parameters to ensure the best possible performance of the function.

5. How do you know if the parameters you have chosen are truly optimal?

To determine if the chosen parameters are truly optimal, it is important to thoroughly evaluate the function's performance using various metrics and compare it to alternative parameter values. Additionally, conducting sensitivity analyses can help determine the robustness of the chosen parameters and their impact on the function's output.

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