Search results
Results from the WOW.Com Content Network
Newton's form has the simplicity that the new points are always added at one end: Newton's forward formula can add new points to the right, and Newton's backward formula can add new points to the left. The accuracy of polynomial interpolation depends on how close the interpolated point is to the middle of the x values of the set of points used ...
The backward differentiation formula (BDF) is a family of implicit methods for the numerical integration of ordinary differential equations.They are linear multistep methods that, for a given function and time, approximate the derivative of that function using information from already computed time points, thereby increasing the accuracy of the approximation.
This expression is Newton's difference quotient (also known as a first-order divided difference). The slope of this secant line differs from the slope of the tangent line by an amount that is approximately proportional to h. As h approaches zero, the slope of the secant line approaches the slope of the tangent line.
Since the relationship between divided differences and backward differences is given as: [citation needed] [,, …,] =! (), taking = (), if the representation of x in the previous sections was instead taken to be = +, the Newton backward interpolation formula is expressed as: () = (+) = = () (). which is the interpolation of all points before .
A finite difference is a mathematical expression of the form f (x + b) − f (x + a).If a finite difference is divided by b − a, one gets a difference quotient.The approximation of derivatives by finite differences plays a central role in finite difference methods for the numerical solution of differential equations, especially boundary value problems.
This is the Euler method (or forward Euler method, in contrast with the backward Euler method, to be described below). The method is named after Leonhard Euler who described it in 1768. The Euler method is an example of an explicit method. This means that the new value y n+1 is defined in terms of things that are already known, like y n.
Iterative methods such as Newton's method are often used to solve the implicit formula. Sometimes an explicit multistep method is used to "predict" the value of +. That value is then used in an implicit formula to "correct" the value. The result is a predictor–corrector method.
for + (compare this with formula (3) where + was given explicitly rather than as an unknown in an equation). This is a quadratic equation , having one negative and one positive root . The positive root is picked because in the original equation the initial condition is positive, and then y {\displaystyle y} at the next time step is given by