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Symmetric matrices --- Eigenvalues --- Symmetric matrices. --- Eigenvalues.
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Eigenvalues. --- Feedback control systems --- Design and construction. --- Eigenvalues
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Mathematical analysis --- Eigenvalues --- Differential operators --- Orthogonal polynomials --- Congresses --- Eigenvalues. --- Fourier analysis --- Functions, Orthogonal --- Polynomials --- Operators, Differential --- Differential equations --- Operator theory --- Matrices --- Differential operators - Congresses --- Orthogonal polynomials - Congresses
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Eigenvalues. --- Numerical analysis. --- Matrices. --- Structural dynamics. --- Valeurs propres. --- Analyse numérique matricielle. --- Constructions --- Dynamique
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Differential equations --- Partial differential operators. --- Opérateurs différentiels partiels. --- Eigenvalues. --- Valeurs propres. --- Differential equations, Hypoelliptic. --- Équations différentielles hypoelliptiques. --- Asymptotic expansions. --- Développements asymptotiques. --- Asymptotic expansions --- Differential equations, Hypoelliptic --- Eigenvalues --- Partial differential operators --- Differential operators --- Matrices --- Hypoelliptic differential equations --- Differential equations, Partial --- Asymptotic developments --- Asymptotes --- Convergence --- Difference equations --- Divergent series --- Functions --- Numerical analysis
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Proefschriften --- Thèses --- Academic collection --- #BIBC:T1998 --- 519.6 --- 681.3*G13 --- Computational mathematics. Numerical analysis. Computer programming --- Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- Theses --- 681.3*G13 Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- 519.6 Computational mathematics. Numerical analysis. Computer programming
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Eigenvalues --- Data processing. --- ARPACK (Computer file) --- 519.6 --- 681.3*G13 --- Computational mathematics. Numerical analysis. Computer programming --- Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- 681.3*G13 Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- ARPACK (Computer file). --- Matrices --- Data processing --- Algorithmes --- Analyse numérique. --- Numerical analysis --- Algorithms --- Itération (mathématiques) --- Iterative methods (Mathematics) --- Analyse numérique --- Numerical analysis. --- Algorithms. --- Itération (mathématiques) --- Valeurs propres --- Estimation numerique
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High performance computing. --- Algebras, Linear --- Superinformatique --- Algèbre linéaire --- Data processing. --- Informatique --- 519.6 --- 681.3*G13 --- Computational mathematics. Numerical analysis. Computer programming --- Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- 681.3*G13 Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- Algèbre linéaire --- High performance computing --- HPC (Computer science) --- Electronic data processing --- Cyberinfrastructure --- Supercomputers --- Data processing --- Itération (mathématiques) --- Analyse numérique. --- Numerical analysis --- Iterative methods (Mathematics) --- Algèbre linéaire. --- Itération (mathématiques) --- Analyse numérique. --- Algèbre linéaire.
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Here is an overview of modern computational stabilization methods for linear inversion, with applications to a variety of problems in audio processing, medical imaging, seismology, astronomy, and other areas. Rank-deficient problems involve matrices that are exactly or nearly rank deficient. Such problems often arise in connection with noise suppression and other problems where the goal is to suppress unwanted disturbances of given measurements. Discrete ill-posed problems arise in connection with the numerical treatment of inverse problems, where one typically wants to compute information about interior properties using exterior measurements. Examples of inverse problems are image restoration and tomography, where one needs to improve blurred images or reconstruct pictures from raw data. This book describes new and existing numerical methods for the analysis and solution of rank-deficient and discrete ill-posed problems. The emphasis is on insight into the stabilizing properties of the algorithms and the efficiency and reliability of the computations.
Equations, Simultaneous --- Iterative methods (Mathematics) --- Sparse matrices. --- Itération (Mathématiques) --- Matrices éparses --- Numerical solutions. --- 519.6 --- 681.3*G13 --- 517.95 --- #TELE:SISTA --- 681.3*G15 --- Computational mathematics. Numerical analysis. Computer programming --- Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- Partial differential equations --- Roots of nonlinear equations: convergence; error analysis; iterative methods;polynomials (Numerical analysis) --- 681.3*G15 Roots of nonlinear equations: convergence; error analysis; iterative methods;polynomials (Numerical analysis) --- 517.95 Partial differential equations --- 681.3*G13 Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- Iterative methods (Mathematics). --- Itération (Mathématiques) --- Matrices éparses --- Sparse matrices --- Spare matrix techniques --- Matrices --- Iteration (Mathematics) --- Numerical analysis --- Numerical solutions --- Equations, Simultaneous - Numerical solutions.
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Reciprocity laws of various kinds play a central role in number theory. In the easiest case, one obtains a transparent formulation by means of roots of unity, which are special values of exponential functions. A similar theory can be developed for special values of elliptic or elliptic modular functions, and is called complex multiplication of such functions. In 1900 Hilbert proposed the generalization of these as the twelfth of his famous problems. In this book, Goro Shimura provides the most comprehensive generalizations of this type by stating several reciprocity laws in terms of abelian varieties, theta functions, and modular functions of several variables, including Siegel modular functions. This subject is closely connected with the zeta function of an abelian variety, which is also covered as a main theme in the book. The third topic explored by Shimura is the various algebraic relations among the periods of abelian integrals. The investigation of such algebraicity is relatively new, but has attracted the interest of increasingly many researchers. Many of the topics discussed in this book have not been covered before. In particular, this is the first book in which the topics of various algebraic relations among the periods of abelian integrals, as well as the special values of theta and Siegel modular functions, are treated extensively.
Ordered algebraic structures --- 512.74 --- Abelian varieties --- Modular functions --- Functions, Modular --- Elliptic functions --- Group theory --- Number theory --- Varieties, Abelian --- Geometry, Algebraic --- Algebraic groups. Abelian varieties --- 512.74 Algebraic groups. Abelian varieties --- Abelian varieties. --- Modular functions. --- Abelian extension. --- Abelian group. --- Abelian variety. --- Absolute value. --- Adele ring. --- Affine space. --- Affine variety. --- Algebraic closure. --- Algebraic equation. --- Algebraic extension. --- Algebraic number field. --- Algebraic structure. --- Algebraic variety. --- Analytic manifold. --- Automorphic function. --- Automorphism. --- Big O notation. --- CM-field. --- Characteristic polynomial. --- Class field theory. --- Coefficient. --- Complete variety. --- Complex conjugate. --- Complex multiplication. --- Complex number. --- Complex torus. --- Corollary. --- Degenerate bilinear form. --- Differential form. --- Direct product. --- Direct proof. --- Discrete valuation ring. --- Divisor. --- Eigenvalues and eigenvectors. --- Embedding. --- Endomorphism. --- Existential quantification. --- Field of fractions. --- Finite field. --- Fractional ideal. --- Function (mathematics). --- Fundamental theorem. --- Galois extension. --- Galois group. --- Galois theory. --- Generic point. --- Ground field. --- Group theory. --- Groupoid. --- Hecke character. --- Homology (mathematics). --- Homomorphism. --- Identity element. --- Integer. --- Irreducibility (mathematics). --- Irreducible representation. --- Lie group. --- Linear combination. --- Linear subspace. --- Local ring. --- Modular form. --- Natural number. --- Number theory. --- Polynomial. --- Prime factor. --- Prime ideal. --- Projective space. --- Projective variety. --- Rational function. --- Rational mapping. --- Rational number. --- Real number. --- Residue field. --- Riemann hypothesis. --- Root of unity. --- Scientific notation. --- Semisimple algebra. --- Simple algebra. --- Singular value. --- Special case. --- Subgroup. --- Subring. --- Subset. --- Summation. --- Theorem. --- Vector space. --- Zero element.
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