Search results
Results from the WOW.Com Content Network
An illustration of Newton's method. In numerical analysis, the Newton–Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.
Newton's method uses curvature information (i.e. the second derivative) to take a more direct route. In calculus , Newton's method (also called Newton–Raphson ) is an iterative method for finding the roots of a differentiable function f {\displaystyle f} , which are solutions to the equation f ( x ) = 0 {\displaystyle f(x)=0} .
If instead one performed Newton-Raphson iterations beginning with an estimate of 10, it would take two iterations to get to 3.66, matching the hyperbolic estimate. For a more typical case like 75, the hyperbolic estimate of 8.00 is only 7.6% low, and 5 Newton-Raphson iterations starting at 75 would be required to obtain a more accurate result.
Newton's method assumes the function f to have a continuous derivative. Newton's method may not converge if started too far away from a root. However, when it does converge, it is faster than the bisection method; its order of convergence is usually quadratic whereas the bisection method's is linear. Newton's method is also important because it ...
Newton–Raphson uses Newton's method to find the reciprocal of and multiply that reciprocal by to find the final quotient . The steps of Newton–Raphson division are: Calculate an estimate X 0 {\displaystyle X_{0}} for the reciprocal 1 / D {\displaystyle 1/D} of the divisor D {\displaystyle D} .
One way of calculating and is to use Heron's method, which is a special case of Newton's method, to find a solution for the equation =, giving the iterative formula + = (+),, > The sequence { x k } {\displaystyle \{x_{k}\}} converges quadratically to n {\displaystyle {\sqrt {n}}} as k → ∞ {\displaystyle k\to \infty } .
The backward Euler method is an implicit method, meaning that we have to solve an equation to find y n+1. One often uses fixed-point iteration or (some modification of) the Newton–Raphson method to achieve this.
Newton–Raphson division: uses Newton's method to find the reciprocal of D, and multiply that reciprocal by N to find the final quotient Q. Goldschmidt division; Exponentiation: Exponentiation by squaring; Addition-chain exponentiation; Multiplicative inverse Algorithms: for computing a number's multiplicative inverse (reciprocal). Newton's method