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Singular Value
In mathematics, in particular functional analysis, the singular values, or ''s''-numbers of a compact operator T: X \rightarrow Y acting between Hilbert spaces X and Y, are the square roots of the (necessarily non-negative) eigenvalues of the self-adjoint operator T^*T (where T^* denotes the adjoint of T). The singular values are non-negative real numbers, usually listed in decreasing order (''σ''1(''T''), ''σ''2(''T''), …). The largest singular value ''σ''1(''T'') is equal to the operator norm of ''T'' (see Min-max theorem). If ''T'' acts on Euclidean space \Reals ^n, there is a simple geometric interpretation for the singular values: Consider the image by T of the unit sphere; this is an ellipsoid, and the lengths of its semi-axes are the singular values of T (the figure provides an example in \Reals^2). The singular values are the absolute values of the eigenvalues of a normal matrix ''A'', because the spectral theorem can be applied to obtain unitary diagonalization ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mathematics
Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics with the major subdisciplines of number theory, algebra, geometry, and analysis, respectively. There is no general consensus among mathematicians about a common definition for their academic discipline. Most mathematical activity involves the discovery of properties of abstract objects and the use of pure reason to prove them. These objects consist of either abstractions from nature orin modern mathematicsentities that are stipulated to have certain properties, called axioms. A ''proof'' consists of a succession of applications of deductive rules to already established results. These results include previously proved theorems, axioms, andin case of abstraction from naturesome basic properties that are considered true starting points of t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Schatten Norm
In mathematics, specifically functional analysis, the Schatten norm (or Schatten–von-Neumann norm) arises as a generalization of ''p''-integrability similar to the trace class norm and the Hilbert–Schmidt norm. Definition Let H_1, H_2 be Hilbert spaces, and T a (linear) bounded operator from H_1 to H_2. For p\in T\, _ = [\mathrm (, T, ^p). If T is compact and H_1,\,H_2 are separable, then : \, T\, _ := \bigg( \sum _ s^p_n(T)\bigg)^ for s_1(T) \ge s_2(T) \ge \cdots s_n(T) \ge \cdots \ge 0 the singular values of T, i.e. the eigenvalues of the Hermitian operator , T, :=\sqrt. Properties In the following we formally extend the range of p to ,\infty/math> with the convention that \, \cdot\, _ is the operator norm. The dual index to p=\infty is then q=1. * The Schatten norms are unitarily invariant: for unitary operators U and V and p\in ,\infty/math>, :: \, U T V\, _p = \, T\, _p. * They satisfy Hölder's inequality: for all p\in ,\infty/math> and q ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Condition Number
In numerical analysis, the condition number of a function measures how much the output value of the function can change for a small change in the input argument. This is used to measure how sensitive a function is to changes or errors in the input, and how much error in the output results from an error in the input. Very frequently, one is solving the inverse problem: given f(x) = y, one is solving for ''x,'' and thus the condition number of the (local) inverse must be used. In linear regression the condition number of the moment matrix can be used as a diagnostic for multicollinearity. The condition number is an application of the derivative, and is formally defined as the value of the asymptotic worst-case relative change in output for a relative change in input. The "function" is the solution of a problem and the "arguments" are the data in the problem. The condition number is frequently applied to questions in linear algebra, in which case the derivative is straightforward b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Banach Space
In mathematics, more specifically in functional analysis, a Banach space (pronounced ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vectors and is complete in the sense that a Cauchy sequence of vectors always converges to a well-defined limit that is within the space. Banach spaces are named after the Polish mathematician Stefan Banach, who introduced this concept and studied it systematically in 1920–1922 along with Hans Hahn and Eduard Helly. Maurice René Fréchet was the first to use the term "Banach space" and Banach in turn then coined the term " Fréchet space." Banach spaces originally grew out of the study of function spaces by Hilbert, Fréchet, and Riesz earlier in the century. Banach spaces play a central role in functional analysis. In other areas of analysis, the spaces under study are often Banach spaces. Definition A Banach space is a complete n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mark Krein
Mark Grigorievich Krein ( uk, Марко́ Григо́рович Крейн, russian: Марк Григо́рьевич Крейн; 3 April 1907 – 17 October 1989) was a Soviet mathematician, one of the major figures of the Soviet school of functional analysis. He is known for works in operator theory (in close connection with concrete problems coming from mathematical physics), the problem of moments, classical analysis and representation theory. He was born in Kyiv, leaving home at age 17 to go to Odessa. He had a difficult academic career, not completing his first degree and constantly being troubled by anti-Semitic discrimination. His supervisor was Nikolai Chebotaryov. He was awarded the Wolf Prize in Mathematics in 1982 (jointly with Hassler Whitney), but was not allowed to attend the ceremony. David Milman, Mark Naimark, Israel Gohberg, Vadym Adamyan, Mikhail Livsic and other known mathematicians were his students. He died in Odessa. On 14 January 2008, the memo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Israel Gohberg
Israel Gohberg ( he, ישראל גוכברג; russian: Изра́иль Цу́дикович Го́хберг; 23 August 1928 – 12 October 2009) was a Bessarabian-born Soviet and Israeli mathematician, most known for his work in operator theory and functional analysis, in particular linear operators and integral equations. Biography Gohberg was born in Tarutyne to parents Tsudik and Haya Gohberg. His father owned a small typography shop and his mother was a midwife. The young Gohberg studied in a Hebrew school in Taurtyne and then a Romanian school in Orhei, where he was influenced by the tutelage of Modest Shumbarsky, a student of the renowned topologist Karol Borsuk. He studied at the Kyrgyz Pedagogical Institute in Bishkek and the University of Chişinău, completed his doctorate at Leningrad University on a thesis advised by Mark Krein (1954), and attended the University of Moscow for his habilitation degree. Gohberg joined the faculty at Teacher's college in Soroki ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Erhard Schmidt
Erhard Schmidt (13 January 1876 – 6 December 1959) was a Baltic German mathematician whose work significantly influenced the direction of mathematics in the twentieth century. Schmidt was born in Tartu (german: link=no, Dorpat), in the Governorate of Livonia (now Estonia). Mathematics His advisor was David Hilbert and he was awarded his doctorate from University of Göttingen in 1905. His doctoral dissertation was entitled ''Entwickelung willkürlicher Funktionen nach Systemen vorgeschriebener'' and was a work on integral equations. Together with David Hilbert he made important contributions to functional analysis. Ernst Zermelo credited conversations with Schmidt for the idea and method for his classic 1904 proof of the Well-ordering theorem from an "Axiom of choice", which has become an integral part of modern set theory. After the war, in 1948, Schmidt founded and became the first editor-in-chief of the journal ''Mathematische Nachrichten''. National Socialism During ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Weyl's Inequality
In linear algebra, Weyl's inequality is a theorem about the changes to eigenvalues of an Hermitian matrix that is perturbed. It can be used to estimate the eigenvalues of a perturbed Hermitian matrix. Weyl's inequality about perturbation Let M=N+R,\,N, and R be ''n''×''n'' Hermitian matrices, with their respective eigenvalues \mu_i,\,\nu_i,\,\rho_i ordered as follows: :M:\quad \mu_1 \ge \cdots \ge \mu_n, :N:\quad\nu_1 \ge \cdots \ge \nu_n, :R:\quad\rho_1 \ge \cdots \ge \rho_n. Then the following inequalities hold: :\nu_i + \rho_n \le \mu_i \le \nu_i + \rho_1,\quad i=1,\dots,n, and, more generally, :\nu_j + \rho_k \le \mu_i \le \nu_r + \rho_s,\quad j+k-n \ge i \ge r+s-1. In particular, if R is positive definite then plugging \rho_n > 0 into the above inequalities leads to :\mu_i > \nu_i \quad \forall i = 1,\dots,n. Note that these eigenvalues can be ordered, because they are real (as eigenvalues of Hermitian matrices). Weyl's inequality between eigenvalues and singular val ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Charles Royal Johnson
Charles Royal Johnson (born January 28, 1948) is an American mathematician specializing in linear algebra. He is a Class of 1961 professor of mathematics at College of William and Mary. The books ''Matrix Analysis'' and ''Topics in Matrix Analysis'', co-written by him with Roger Horn, are standard texts in advanced linear algebra. Career Charles R. Johnson received a B.A. with distinction in Mathematics and Economics from Northwestern University in 1969. In 1972, he received a Ph.D. in Mathematics and Economics from the California Institute of Technology, where he was advised by Olga Taussky Todd; his dissertation was entitled "Matrices whose Hermitian Part is Positive Definite". Johnson held various professorships over ten years at the University of Maryland, College Park starting in 1974. He was a professor at Clemson University from 1984 to 1987. In 1987, he became a professor of mathematics at the College of William and Mary The College of William & Mary (officially Th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Roger Horn
Roger Alan Horn (born January 19, 1942) is an American mathematician specializing in matrix analysis. He was research professor of mathematics at the University of Utah. He is known for formulating the Bateman–Horn conjecture with Paul T. Bateman on the density of prime number values generated by systems of polynomials. His books ''Matrix Analysis'' and ''Topics in Matrix Analysis'', co-written with Charles R. Johnson, are standard texts in advanced linear algebra. Career Roger Horn graduated from Cornell University with high honors in mathematics in 1963, after which he completed his PhD at Stanford University in 1967. Horn was the founder and chair of the Department of Mathematical Sciences at Johns Hopkins University from 1972 to 1979. As chair, he held a series of short courses for a monograph series published by the Johns Hopkins Press. He invited Gene Golub and Charles Van Loan to write a monograph, which later became the seminal ''Matrix Computations'' text book. He l ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trace (linear Algebra)
In linear algebra, the trace of a square matrix , denoted , is defined to be the sum of elements on the main diagonal (from the upper left to the lower right) of . The trace is only defined for a square matrix (). It can be proved that the trace of a matrix is the sum of its (complex) eigenvalues (counted with multiplicities). It can also be proved that for any two matrices and . This implies that similar matrices have the same trace. As a consequence one can define the trace of a linear operator mapping a finite-dimensional vector space into itself, since all matrices describing such an operator with respect to a basis are similar. The trace is related to the derivative of the determinant (see Jacobi's formula). Definition The trace of an square matrix is defined as \operatorname(\mathbf) = \sum_^n a_ = a_ + a_ + \dots + a_ where denotes the entry on the th row and th column of . The entries of can be real numbers or (more generally) complex numbers. The trace is not ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Singular Value Decomposition
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any \ m \times n\ matrix. It is related to the polar decomposition. Specifically, the singular value decomposition of an \ m \times n\ complex matrix is a factorization of the form \ \mathbf = \mathbf\ , where is an \ m \times m\ complex unitary matrix, \ \mathbf\ is an \ m \times n\ rectangular diagonal matrix with non-negative real numbers on the diagonal, is an n \times n complex unitary matrix, and \ \mathbf\ is the conjugate transpose of . Such decomposition always exists for any complex matrix. If is real, then and can be guaranteed to be real orthogonal matrices; in such contexts, the SVD is often denoted \ \mathbf^\mathsf\ . The diagonal entries \ \sigma_i = \Sigma_\ of \ \mathbf\ are uniquely determined by and are known as the singular values ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
