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An initial value problem is a differential equation ′ = (, ()) with : where is an open set of , together with a point in the domain of (,),called the initial condition.. A solution to an initial value problem is a function that is a solution to the differential equation and satisfies
The fixed point iteration x n+1 = cos x n with initial value x 1 = −1.. An attracting fixed point of a function f is a fixed point x fix of f with a neighborhood U of "close enough" points around x fix such that for any value of x in U, the fixed-point iteration sequence , (), (()), ((())), … is contained in U and converges to x fix.
In mathematical analysis, the initial value theorem is a theorem used to relate frequency domain expressions to the time domain behavior as time approaches zero. [1] Let = be the (one-sided) Laplace transform of ƒ(t).
For the equation and initial value problem: ′ = (,), = if and / are continuous in a closed rectangle = [, +] [, +] in the plane, where and are real (symbolically: ,) and denotes the Cartesian product, square brackets denote closed intervals, then there is an interval = [, +] [, +] for some where the solution to the above equation and initial ...
The above equations are, in fact, the general functions sought, but they are in their general form (with unspecified values of A and B), whilst we want to actually find their exact forms and solutions. So now we consider the problem’s given initial conditions (the problem including given initial conditions is the so-called initial value problem).
Good explanations of the initial and final value theorems Archived 2009-01-08 at the Wayback Machine; Laplace Transforms at MathPages; Computational Knowledge Engine allows to easily calculate Laplace Transforms and its inverse Transform. Laplace Calculator to calculate Laplace Transforms online easily.
If an equation can be put into the form f(x) = x, and a solution x is an attractive fixed point of the function f, then one may begin with a point x 1 in the basin of attraction of x, and let x n+1 = f(x n) for n ≥ 1, and the sequence {x n} n ≥ 1 will converge to the solution x.
The geometric interpretation of Newton's method is that at each iteration, it amounts to the fitting of a parabola to the graph of () at the trial value , having the same slope and curvature as the graph at that point, and then proceeding to the maximum or minimum of that parabola (in higher dimensions, this may also be a saddle point), see below.