Conjugate Gradient Method (Solving Quadratic Equations with Two Varaibles)
The code highlights the Fletcher Reeve's Method or Conjugate Gradient Method. This method exploits the advantage of conjugate directions and hence is quadratically convergent. It takes only 3 iterations or 2 searches to solve a quadratic equation. The optimum for the same example as shown in this algorithm took 56 iterations with Steepest Descent.(Refer Steepest Descent Code); while this algorithm converges in only 3 iterations same initial guess or start point.
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Soumitra Sitole (2024). Conjugate Gradient Method (Solving Quadratic Equations with Two Varaibles) (https://www.mathworks.com/matlabcentral/fileexchange/62011-conjugate-gradient-method-solving-quadratic-equations-with-two-varaibles), MATLAB Central File Exchange. Récupéré le .
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A inspiré : Modified Conjugate Gradient Method (Bivariate optimization)
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