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Springer Optimization and Its Applications Ser.: Smoothing Techniques for Curve Estimation by M. Rosenblatt (2008, Hardcover)
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About this product
Product Identifiers
PublisherSpringer New York
ISBN-100387097066
ISBN-139780387097060
eBay Product ID (ePID)2115720
Product Key Features
Number of PagesXxiv, 274 Pages
Publication NameSmoothing Techniques for Curve Estimation
LanguageEnglish
Publication Year2008
SubjectProbability & Statistics / General, Computer Science, Operations Research, Geometry / Algebraic
TypeTextbook
Subject AreaMathematics, Computers, Business & Economics
AuthorM. Rosenblatt
SeriesSpringer Optimization and Its Applications Ser.
FormatHardcover
Dimensions
Item Weight46.6 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
Dewey Edition22
ReviewsFrom the reviews: "This book reflects the state of the art in parallel algorithms and their implementation for solving optimization problems and applications involving such problems. ... the volume is recommended for graduate students and researchers in applied mathematics and computer science. Scientists engaged in parallel scientific computing ... welcome this compilation of latest achievements in this field." (Dana Petcu, Mathematical Reviews, Issue 2009 m), From the reviews:"This book reflects the state of the art in parallel algorithms and their implementation for solving optimization problems and applications involving such problems. … the volume is recommended for graduate students and researchers in applied mathematics and computer science. Scientists engaged in parallel scientific computing … welcome this compilation of latest achievements in this field." (Dana Petcu, Mathematical Reviews, Issue 2009 m)
Series Volume Number27
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal004.35
Table Of ContentParallel Algorithms for Matrix Computations.- RECSY and SCASY Library Software: Recursive Blocked and Parallel Algorithms for Sylvester-Type Matrix Equations with Some Applications.- Parallelization of Linear Algebra Algorithms Using ParSol Library of Mathematical Objects.- The Development of an Object-Oriented Parallel Block Preconditioning Framework.- A Sparse Linear System Solver Used in a Distributed and Heterogenous Grid Computing Environment.- Parallel Diagonalization Performance on High-Performance Computers.- Parallel Optimization.- Parallel Global Optimization in Multidimensional Scaling.- High-Performance Parallel Support Vector Machine Training.- Parallel Branch and Bound Algorithm with Combination of Lipschitz Bounds over Multidimensional Simplices for Multicore Computers.- Experimental Investigation of Local Searches for Optimization of Grillage-Type Foundations.- Management of Parallel Programming Models and Data.- Comparison of the UK National Supercomputer Services: HPCx and HECToR.- DL_POLY_3 I/O: Analysis, Alternatives, and Future Strategies.- Mixed Mode Programming on HPCx.- A Structure Conveying Parallelizable Modeling Language for Mathematical Programming.- Computational Requirements for Pulsar Searches with the Square Kilometer Array.- Parallel Scientific Computing in Industrial Applications.- Parallel Multiblock Multigrid Algorithms for Poroelastic Models.- A Parallel Solver for the 3D Simulation of Flows Through Oil Filters.- High-Performance Computing in Jet Aerodynamics.- Parallel Numerical Solver for the Simulation of the Heat Conduction in Electrical Cables.- Orthogonalization Procedure for Antisymmetrization of J-shell States.- Parallel Direct Numerical Simulation of an Annular Gas-Liquid Two-Phase Jet with Swirl.- Parallel NumericalAlgorithm for the Traveling Wave Model.- Parallel Algorithm for Cell Dynamics Simulation of Soft Nano-Structured Matter.- Docking and Molecular Dynamics Simulation of Complexes of High and Low Reactive Substrates with Peroxidases.
SynopsisParallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including survey chapters and surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix computations, parallel optimization, management of parallel programming models and data, with the largest focus on parallel scientific computing in industrial applications. This volume is intended for scientists and graduate students specializing in computer science and applied mathematics who are engaged in parallel scientific computing., The book is divided into four parts: Parallel Algorithms for Matrix Computations, Parallel Optimization, Management of Parallel Programming Models and Data, and Parallel Scienti'c Computing in Industrial Applications. The ?rst part of the book includes chapters on parallel matrix computations. The chapter by R. Granat, I. Jonsson, and B. Kagstr ? om, ¨ "RECSY and SCASY Library Software: Recursive Blocked and Parallel Algorithms for Sylvester-type Matrix Equations with Some Applications", gives an overview of state-of-the-art high-performance computing (HPC) algorithms and software for solving various standard and generalized Sylvester-type matrix equations. Computer-aided control system design (CACSD) is a great source of applications for matrix equations - cluding different eigenvalue and subspace problems and for condition estimation. The parallelization is invoked at two levels: globally in a distributed memory paradigm, and locally on shared memory or multicore nodes as part of the d- tributed memory environment. ? In the chapter by A. Jakuse ? v, R. Ciegis, I. Laukaityte, ? and V. Tro'mov, "P- allelization of Linear Algebra Algorithms Using ParSol Library of Mathematical Objects", the mathematical objects library ParSol is described and evaluated. It is applied to implement the ?nite difference scheme to solve numerically a s- tem of PDEs describing a nonlinear interaction of two counter-propagating laser waves., This book introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. It includes surveys written by 23 notable researchers in the field and a wide range of industrial applications.
LC Classification NumberQA273.A1-274.9
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