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In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank

Nonlinear systems --- Mathematical models. --- Systems, Nonlinear --- System theory --- Calculus of variations. --- Eigenvalues. --- Calculus of variations --- Eigenvalues

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Multiparameter eigenvalue problems

Differential equations. --- Eigenvalues. --- Inverse problems (Differential equations). --- Matrices. --- Operator theory. --- Spectral theory (Mathematics). --- Sturm-Liouville equation. --- Algebras, Linear. --- Compact operators --- Algèbre linéaire --- Matrices --- Opérateurs compacts --- Valeurs propres --- Eigenvalues --- Differential equations

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Matrix Singular Value Decomposition (SVD) and its application to problems in signal processing is explored in this book. The papers discuss algorithms and implementation architectures for computing the SVD, as well as a variety of applications such as systems and signal modeling and detection. The publication presents a number of keynote papers, highlighting recent developments in the field, namely large scale SVD applications, isospectral matrix flows, Riemannian SVD and consistent signal reconstruction. It also features a translation of a historical paper by Eugenio Beltrami, containing on

Signal processing --- Decomposition (Mathematics) --- Digital techniques --- Congresses --- -Signal processing --- -Academic collection --- #TELE:SISTA --- 519.6 --- 681.3*G13 --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Mathematics --- Probabilities --- -Congresses --- Computational mathematics. Numerical analysis. Computer programming --- 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 --- 681.3*G13 Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems --- Academic collection --- Digital techniques&delete& --- Decomposition (Mathematics) - Congresses. --- Signal processing - Digital techniques - Congresses --- Decomposition (Mathematics) - Congresses --- Signals --- Processing

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The solutions of systems of linear and nonlinear equations occurs in many situations and is therefore a question of major interest. Advances in computer technology has made it now possible to consider systems exceeding several hundred thousands of equations. However, there is a crucial need for more efficient algorithms.

The main focus of this book (except the last chapter, which is devoted to systems of nonlinear equations) is the consideration of solving the problem of the linear equation Ax = b by an iterative method. Iterative methods for the solution of this question are described which are based on projections. Recently, such methods have received much attention from researchers in numerical linear algebra and have been applied to a wide range of problems.

The book is intended for students and researchers in numerical analysis and for practitioners and engineers who require the most recent methods for solving their particular problem.

Lineaire vergelijkingen. --- Projectiemethoden (wiskunde) --- Equations, Simultaneous --- Iterative methods (Mathematics) --- Itération (Mathématiques) --- Numerical solutions. --- -Iterative methods (Mathematics) --- #TELE:SISTA --- 519.6 --- 681.3*G13 --- Iteration (Mathematics) --- Numerical analysis --- Simultaneous equations --- Numerical solutions --- 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 --- Mathematics --- Physical Sciences & Mathematics --- Algebra --- Equations, Simultaneous - Numerical solutions.

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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics.Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the

Stochastic programming --- Algorithms --- Combinatorial analysis --- Programmation stochastique --- Algorithmes --- Analyse combinatoire --- 681.3*G13 --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- Linear programming --- Combinatorics --- Algebra --- Mathematical analysis --- Algorism --- Arithmetic --- Foundations --- Algorithmes. --- Programmation stochastique. --- Analyse combinatoire. --- Algorithms. --- Combinatorial analysis. --- Stochastic programming.