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Mean Value Theorem (divided Differences)
In mathematical analysis, the mean value theorem for divided differences generalizes the mean value theorem to higher derivatives. Statement of the theorem For any ''n'' + 1 pairwise distinct points ''x''0, ..., ''x''''n'' in the domain of an ''n''-times differentiable function ''f'' there exists an interior point : \xi \in (\min\,\max\) \, where the ''n''th derivative of ''f'' equals ''n'' ! times the ''n''th divided difference at these points: : f _0,\dots,x_n= \frac. For ''n'' = 1, that is two function points, one obtains the simple mean value theorem. Proof Let P be the Lagrange interpolation polynomial for ''f'' at ''x''0, ..., ''x''''n''. Then it follows from the Newton form of P that the highest order term of P is f _0,\dots,x_n^n. Let g be the remainder of the interpolation, defined by g = f - P. Then g has n+1 zeros: ''x''0, ..., ''x''''n''. By applying Rolle's theorem first to g, then to g', and so on un ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mathematical Analysis
Analysis is the branch of mathematics dealing with continuous functions, limit (mathematics), limits, and related theories, such as Derivative, differentiation, Integral, integration, measure (mathematics), measure, infinite sequences, series (mathematics), series, and analytic functions. These theories are usually studied in the context of Real number, real and Complex number, complex numbers and Function (mathematics), functions. Analysis evolved from calculus, which involves the elementary concepts and techniques of analysis. Analysis may be distinguished from geometry; however, it can be applied to any Space (mathematics), space of mathematical objects that has a definition of nearness (a topological space) or specific distances between objects (a metric space). History Ancient Mathematical analysis formally developed in the 17th century during the Scientific Revolution, but many of its ideas can be traced back to earlier mathematicians. Early results in analysis were ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mean Value Theorem
In mathematics, the mean value theorem (or Lagrange's mean value theorem) states, roughly, that for a given planar arc (geometry), arc between two endpoints, there is at least one point at which the tangent to the arc is parallel to the secant line, secant through its endpoints. It is one of the most important results in real analysis. This theorem is used to prove statements about a function on an interval (mathematics), interval starting from local hypotheses about derivatives at points of the interval. History A special case of this theorem for inverse interpolation of the sine was first described by Parameshvara (1380–1460), from the Kerala School of Astronomy and Mathematics in India, in his commentaries on Govindasvāmi and Bhāskara II. A restricted form of the theorem was proved by Michel Rolle in 1691; the result was what is now known as Rolle's theorem, and was proved only for polynomials, without the techniques of calculus. The mean value theorem in its modern for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Divided Difference
In mathematics, divided differences is an algorithm, historically used for computing tables of logarithms and trigonometric functions. Charles Babbage's difference engine, an early mechanical calculator, was designed to use this algorithm in its operation. Divided differences is a recursive division process. Given a sequence of data points (x_0, y_0), \ldots, (x_, y_), the method calculates the coefficients of the interpolation polynomial of these points in the Newton form. It is sometimes denoted by a delta with a bar: \text \!\!\!, \,\, or \text \! \text. Definition Given ''n'' + 1 data points (x_0, y_0),\ldots,(x_, y_) where the x_k are assumed to be pairwise distinct, the forward divided differences are defined as: \begin \mathopen _k&:= y_k, && k \in \ \\ \mathopen _k,\ldots,y_&:= \frac, && k\in\,\ j\in\. \end To make the recursive process of computation clearer, the divided differences can be put in tabular form, where the columns correspond to the value of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lagrange Interpolation Polynomial
In numerical analysis, the Lagrange interpolating polynomial is the unique polynomial of lowest degree that interpolates a given set of data. Given a data set of coordinate pairs (x_j, y_j) with 0 \leq j \leq k, the x_j are called ''nodes'' and the y_j are called ''values''. The Lagrange polynomial L(x) has degree \leq k and assumes each value at the corresponding node, L(x_j) = y_j. Although named after Joseph-Louis Lagrange, who published it in 1795, the method was first discovered in 1779 by Edward Waring. It is also an easy consequence of a formula published in 1783 by Leonhard Euler. Uses of Lagrange polynomials include the Newton–Cotes method of numerical integration, Shamir's secret sharing scheme in cryptography, and Reed–Solomon error correction in coding theory. For equispaced nodes, Lagrange interpolation is susceptible to Runge's phenomenon of large oscillation. Definition Given a set of k + 1 nodes \, which must all be distinct, x_j \neq x_m for indices ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Newton Polynomial
In the mathematical field of numerical analysis, a Newton polynomial, named after its inventor Isaac Newton, is an interpolation polynomial for a given set of data points. The Newton polynomial is sometimes called Newton's divided differences interpolation polynomial because the coefficients of the polynomial are calculated using Newton's divided differences method. Definition Given a set of ''k'' + 1 data points :(x_0, y_0),\ldots,(x_j, y_j),\ldots,(x_k, y_k) where no two ''x''''j'' are the same, the Newton interpolation polynomial is a linear combination of Newton basis polynomials :N(x) := \sum_^ a_ n_(x) with the Newton basis polynomials defined as :n_j(x) := \prod_^ (x - x_i) for ''j'' > 0 and n_0(x) \equiv 1. The coefficients are defined as :a_j := _0,\ldots,y_j/math> where _0,\ldots,y_j/math> are the divided differences defined as \begin \mathopen _k&:= y_k, && k \in \ \\ \mathopen _k,\ldots,y_&:= \frac, && k\in\,\ j\in\. \end Thus the Newton polynomi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rolle's Theorem
In calculus, Rolle's theorem or Rolle's lemma essentially states that any real-valued differentiable function that attains equal values at two distinct points must have at least one point, somewhere between them, at which the slope of the tangent line is zero. Such a point is known as a stationary point. It is a point at which the first derivative of the function is zero. The theorem is named after Michel Rolle. Standard version of the theorem If a real-valued function is continuous on a proper closed interval , differentiable on the open interval , and , then there exists at least one in the open interval such that f'(c) = 0. This version of Rolle's theorem is used to prove the mean value theorem, of which Rolle's theorem is indeed a special case. It is also the basis for the proof of Taylor's theorem. History Although the theorem is named after Michel Rolle, Rolle's 1691 proof covered only the case of polynomial functions. His proof did not use the methods of di ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stolarsky Mean
In mathematics, the Stolarsky mean is a generalization of the logarithmic mean. It was introduced by Kenneth B. Stolarsky in 1975. Definition For two positive real numbers x and y the Stolarsky Mean is defined as: : S_p(x,y) = \left \{ \begin{array}{l l} x, & \text{if }x=y, \\ \left({\frac{x^p-y^p}{p (x-y)\right)^{1/(p-1)}, & \text{otherwise}. \end{array} \right . Derivation It is derived from the mean value theorem, which states that a secant line, cutting the graph of a differentiable function f at ( x, f(x) ) and ( y, f(y) ), has the same slope as a line tangent to the graph at some point \xi in the interval ,y/math>. : \exists \xi\in ,y f'(\xi) = \frac{f(x)-f(y)}{x-y} The Stolarsky mean is obtained by : \xi = \left '\right{-1}\left(\frac{f(x)-f(y)}{x-y}\right) when choosing f(x) = x^p. Special cases *\lim_{p\to -\infty} S_p(x,y) is the minimum. *S_{-1}(x,y) is the geometric mean. *\lim_{p\to 0} S_p(x,y) is the logarithmic mean. It can be obtained from the mean val ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
