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Hardy–Littlewood Inequality
In mathematical analysis, the Hardy–Littlewood inequality, named after G. H. Hardy and John Edensor Littlewood, states that if f and g are nonnegative measurable real functions vanishing at infinity that are defined on n-dimensional Euclidean space \mathbb R^n, then :\int_ f(x)g(x) \, dx \leq \int_ f^*(x)g^*(x) \, dx where f^* and g^* are the symmetric decreasing rearrangements of f and g, respectively. The decreasing rearrangement f^* of f is defined via the property that for all r >0 the two super-level sets :E_f(r)=\left\ \quad and \quad E_(r)=\left\ have the same volume (n-dimensional Lebesgue measure) and E_(r) is a ball in \mathbb R^n centered at x=0, i.e. it has maximal symmetry. Proof The layer cake representation allows us to write the general functions f and g in the form f(x)= \int_0^\infty \chi_ \, dr \quad and \quad g(x)= \int_0^\infty \chi_ \, ds where r \mapsto \chi_ equals 1 for rs the indicator functions x \mapsto \chi_(x) and x \map ... [...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 i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Edensor Littlewood
John Edensor Littlewood (9 June 1885 – 6 September 1977) was a British mathematician. He worked on topics relating to analysis, number theory, and differential equations, and had lengthy collaborations with G. H. Hardy, Srinivasa Ramanujan and Mary Cartwright. Biography Littlewood was born on 9 June 1885 in Rochester, Kent, the eldest son of Edward Thornton Littlewood and Sylvia Maud (née Ackland). In 1892, his father accepted the headmastership of a school in Wynberg, Cape Town, in South Africa, taking his family there. Littlewood returned to Britain in 1900 to attend St Paul's School in London, studying under Francis Sowerby Macaulay, an influential algebraic geometer. In 1903, Littlewood entered the University of Cambridge, studying in Trinity College. He spent his first two years preparing for the Tripos examinations which qualify undergraduates for a bachelor's degree where he emerged in 1905 as Senior Wrangler bracketed with James Mercer (Mercer had already ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Measurable Function
In mathematics and in particular measure theory, a measurable function is a function between the underlying sets of two measurable spaces that preserves the structure of the spaces: the preimage of any measurable set is measurable. This is in direct analogy to the definition that a continuous function between topological spaces preserves the topological structure: the preimage of any open set is open. In real analysis, measurable functions are used in the definition of the Lebesgue integral. In probability theory, a measurable function on a probability space is known as a random variable. Formal definition Let (X,\Sigma) and (Y,\Tau) be measurable spaces, meaning that X and Y are sets equipped with respective \sigma-algebras \Sigma and \Tau. A function f:X\to Y is said to be measurable if for every E\in \Tau the pre-image of E under f is in \Sigma; that is, for all E \in \Tau f^(E) := \ \in \Sigma. That is, \sigma (f)\subseteq\Sigma, where \sigma (f) is the σ-algebra gen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Real Functions
In mathematical analysis, and applications in geometry, applied mathematics, engineering, and natural sciences, a function of a real variable is a function whose domain is the real numbers \mathbb, or a subset of \mathbb that contains an interval of positive length. Most real functions that are considered and studied are differentiable in some interval. The most widely considered such functions are the real functions, which are the real-valued functions of a real variable, that is, the functions of a real variable whose codomain is the set of real numbers. Nevertheless, the codomain of a function of a real variable may be any set. However, it is often assumed to have a structure of \mathbb-vector space over the reals. That is, the codomain may be a Euclidean space, a coordinate vector, the set of matrices of real numbers of a given size, or an \mathbb-algebra, such as the complex numbers or the quaternions. The structure \mathbb-vector space of the codomain induces a structure of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Infinity
Infinity is that which is boundless, endless, or larger than any natural number. It is often denoted by the infinity symbol . Since the time of the ancient Greeks, the philosophical nature of infinity was the subject of many discussions among philosophers. In the 17th century, with the introduction of the infinity symbol and the infinitesimal calculus, mathematicians began to work with infinite series and what some mathematicians (including l'Hôpital and Bernoulli) regarded as infinitely small quantities, but infinity continued to be associated with endless processes. As mathematicians struggled with the foundation of calculus, it remained unclear whether infinity could be considered as a number or magnitude and, if so, how this could be done. At the end of the 19th century, Georg Cantor enlarged the mathematical study of infinity by studying infinite sets and infinite numbers, showing that they can be of various sizes. For example, if a line is viewed as the set of all o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dimension
In physics and mathematics, the dimension of a Space (mathematics), mathematical space (or object) is informally defined as the minimum number of coordinates needed to specify any Point (geometry), point within it. Thus, a Line (geometry), line has a dimension of one (1D) because only one coordinate is needed to specify a point on itfor example, the point at 5 on a number line. A Surface (mathematics), surface, such as the Boundary (mathematics), boundary of a Cylinder (geometry), cylinder or sphere, has a dimension of two (2D) because two coordinates are needed to specify a point on itfor example, both a latitude and longitude are required to locate a point on the surface of a sphere. A two-dimensional Euclidean space is a two-dimensional space on the Euclidean plane, plane. The inside of a cube, a cylinder or a sphere is three-dimensional (3D) because three coordinates are needed to locate a point within these spaces. In classical mechanics, space and time are different categ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Euclidean Space
Euclidean space is the fundamental space of geometry, intended to represent physical space. Originally, that is, in Euclid's Elements, Euclid's ''Elements'', it was the three-dimensional space of Euclidean geometry, but in modern mathematics there are Euclidean spaces of any positive integer dimension (mathematics), dimension, including the three-dimensional space and the ''Euclidean plane'' (dimension two). The qualifier "Euclidean" is used to distinguish Euclidean spaces from other spaces that were later considered in physics and modern mathematics. Ancient History of geometry#Greek geometry, Greek geometers introduced Euclidean space for modeling the physical space. Their work was collected by the Greek mathematics, ancient Greek mathematician Euclid in his ''Elements'', with the great innovation of ''mathematical proof, proving'' all properties of the space as theorems, by starting from a few fundamental properties, called ''postulates'', which either were considered as eviden ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Symmetric Decreasing Rearrangement
In mathematics, the symmetric decreasing rearrangement of a function is a function which is symmetric and decreasing, and whose level sets are of the same size as those of the original function. Definition for sets Given a measurable set, A, in \R^n, one defines the ''symmetric rearrangement'' of A, called A^*, as the ball centered at the origin, whose volume (Lebesgue measure) is the same as that of the set A. An equivalent definition is A^* = \left\, where \omega_n is the volume of the unit ball and where , A, is the volume of A. Definition for functions The rearrangement of a non-negative, measurable real-valued function f whose level sets f^(y) (for y \in \R_) have finite measure is f^*(x) = \int_0^\infty \mathbb_(x) \, dt, where \mathbb_A denotes the indicator function of the set A. In words, the value of f^*(x) gives the height t for which the radius of the symmetric rearrangement of \ is equal to x. We have the following motivation for this definition. Because the iden ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
American Mathematical Society
The American Mathematical Society (AMS) is an association of professional mathematicians dedicated to the interests of mathematical research and scholarship, and serves the national and international community through its publications, meetings, advocacy and other programs. The society is one of the four parts of the Joint Policy Board for Mathematics and a member of the Conference Board of the Mathematical Sciences. History The AMS was founded in 1888 as the New York Mathematical Society, the brainchild of Thomas Fiske, who was impressed by the London Mathematical Society on a visit to England. John Howard Van Amringe was the first president and Fiske became secretary. The society soon decided to publish a journal, but ran into some resistance, due to concerns about competing with the American Journal of Mathematics. The result was the ''Bulletin of the American Mathematical Society'', with Fiske as editor-in-chief. The de facto journal, as intended, was influential in in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Layer Cake Representation
In mathematics, the layer cake representation of a non- negative, real-valued measurable function f defined on a measure space (\Omega,\mathcal,\mu) is the formula :f(x) = \int_0^\infty 1_ (x) \, \mathrmt, for all x \in \Omega, where 1_E denotes the indicator function of a subset E\subseteq \Omega and L(f,t) denotes the super-level set :L(f, t) = \. The layer cake representation follows easily from observing that : 1_(x) = 1_(t) and then using the formula :f(x) = \int_0^ \,\mathrmt. The layer cake representation takes its name from the representation of the value f(x) as the sum of contributions from the "layers" L(f,t): "layers"/values t below f(x) contribute to the integral, while values t above f(x) do not. It is a generalization of Cavalieri's principle and is also known under this name. An important consequence of the layer cake representation is the identity \int_\Omega f(x) \, \mathrm\mu(x) = \int_0^ \mu(\)\,\mathrmt, which follows from it by applying the Fubini-Ton ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rearrangement Inequality
In mathematics, the rearrangement inequality states that x_n y_1 + \cdots + x_1 y_n \leq x_ y_1 + \cdots + x_ y_n \leq x_1 y_1 + \cdots + x_n y_n for every choice of real numbers x_1 \leq \cdots \leq x_n \quad \text \quad y_1 \leq \cdots \leq y_n and every permutation x_, \ldots, x_ of x_1, \ldots, x_n. If the numbers are different, meaning that x_1 < \cdots < x_n \quad \text \quad y_1 < \cdots < y_n, then the lower bound is attained only for the permutation which reverses the order, that is, for all and the upper bound is attained only for the identity, that is, for all Note that the rearrangement inequality makes no assumptions on the signs of the real numbers. Applications Many important inequalities can be proved by the rearrangement inequality, such as the[...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chebyshev's Sum Inequality
In mathematics, Chebyshev's sum inequality, named after Pafnuty Chebyshev, states that if :a_1 \geq a_2 \geq \cdots \geq a_n \quad and \quad b_1 \geq b_2 \geq \cdots \geq b_n, then : \sum_^n a_k b_k \geq \left(\sum_^n a_k\right)\!\!\left(\sum_^n b_k\right)\!. Similarly, if :a_1 \leq a_2 \leq \cdots \leq a_n \quad and \quad b_1 \geq b_2 \geq \cdots \geq b_n, then : \sum_^n a_k b_k \leq \left(\sum_^n a_k\right)\!\!\left(\sum_^n b_k\right)\!. Proof Consider the sum :S = \sum_^n \sum_^n (a_j - a_k) (b_j - b_k). The two sequences are non-increasing, therefore and have the same sign for any . Hence . Opening the brackets, we deduce: :0 \leq 2 n \sum_^n a_j b_j - 2 \sum_^n a_j \, \sum_^n b_j, hence :\frac \sum_^n a_j b_j \geq \left( \frac \sum_^n a_j\right)\!\!\left(\frac \sum_^n b_j\right)\!. An alternative proof is simply obtained with the rearrangement inequality, writing that :\sum_^ a_i \sum_^ b_j = \sum_^ \sum_^ a_i b_j =\sum_^\sum_^ a_i b_ = \sum_^ \sum_^ a_i b_ \leq \s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
