Newton's Method for Solving Systems of Many Nonlinear Equations
We will now extend Newton's Method further to systems of many nonlinear equations. Consider the general system of $n$ linear equations in $n$ unknowns:
(1)To simplify explaining Newton's method, we will introduce some shorthand notation. Let $\alpha = \begin{bmatrix} \alpha_1 \\ \alpha_2 \\ \vdots \\ \alpha_n \end{bmatrix}$ be the solution of interest to this system. Let $x^{(0)} = \begin{bmatrix} x_1^{(0)} \\ x_2^{(0)} \\ \vdots \\ x_n^{(0)} \end{bmatrix}$ be an initial approximation to the solution $\alpha$, and let $x^{(k)} = \begin{bmatrix} x_1^{(k)} \\ x_2^{(k)} \\ \vdots \\ x_n^{(k)} \end{bmatrix}$ be the $k^{\mathrm{th}}$ approximation to the solution $\alpha$ from applying Newton's Method. Furthermore, let $\delta^{(k)} = \begin{bmatrix} x_1 - x_1^{(k)} \\ x_2 - x_2^{(k)} \\ \vdots \\ x_n - x_n^{(k)} \end{bmatrix}$.
Define the matrix $F$ applied approximation $x^{(k)}$ to be:
(2)And we will define $F'$ applied to our approximation $x^{(k)}$ to be the matrix of partial derivatives evaluated at the point $x^{(k)}$:
(3)The general iteration of Newton's Method is thus given by:
(4)Furthermore, each successive approximation of the root $\alpha$ is given by:
(5)An equivalent form for each successive approximative $x^{(k+1)}$ of $\alpha$ can be obtained by substituting $\delta^{(k)}$ for $\left [ F'(x^{(k)} \right ]^{-1}$ so then $x^{(k+1)} = x^{(k)} - \left [ F'(x^{(k)} \right ]^{-1} F(x^{(k)}$