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High Performance Algorithms for Structured Matrix Problems

The main aim of this volume is to summarise the state of the art in the area of high performance solutions of structured linear systems as;

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Turbo Message Passing Algorithms for Structured Signal Recovery

This book takes a comprehensive study on turbo message passing algorithms for structured signal recovery, where the considered structured;

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Structure-Preserving Doubling Algorithms for Nonlinear Matrix Equations

queue theory and vibration analysis for high-speed trains. The authors present recent developments and results for the theory of doubling;

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Combinatorial Scientific Computing

in designing software and applications for high-performance computing systems. The book offers a state-of-the-art overview of the latest;

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Combinatorial Scientific Computing

in designing software and applications for high-performance computing systems. The book offers a state-of-the-art overview of the latest;

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Quaternion Matrix Computations

In this monograph, the authors describe state-of-the-art real structure-preserving algorithms for quaternion matrix computations;

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Parallel Processing and Applied Mathematics

efficient computing; workshop on scheduling for parallel computing (SPC 2019); workshop on applied high performance numerical algorithms for PDEs;

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Advances in High Performance Computing

Every day we need to solve large problems for which supercomputers are needed. High performance computing (HPC) is a paradigm that allows;

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Parallel Processing and Applied Mathematics

efficient computing; workshop on scheduling for parallel computing (SPC 2019); workshop on applied high performance numerical algorithms for PDEs;

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Modeling and Optimization of LCD Optical Performance

modeling, ranging from the simple Jones matrix method to elaborate and high accuracy algorithms suitable for off-axis optics. Researchers and;

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Matrix Algorithms

This thorough, concise, and superbly written volume is the first in a self-contained five-volume series devoted to matrix algorithms. It;

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Exploiting Hidden Structure in Matrix Computations: Algorithms and Applications

of efficient numerical methods, for example algorithms for matrices with low-rank block structure, matrices with decay, and structured tensor;

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MM Optimization Algorithms

algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics. Derives numerous algorithms from a;

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Sparse Modeling

formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery. The book gets you;

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Sparse Modeling

, problem formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery. The;

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Numerical Linear Algebra

problems. Developed from a number of courses taught repeatedly by the authors, the material covers topics like matrix algebra, theory for linear;

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Introduction To Matrix Structural Analysis And Finite Element Methods, An

overarching framework of matrix analysis. FEM builds on this foundation with numerical approximation techniques for solving boundary value problems;

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Matrix Computations

The fourth edition of Gene H. Golub and Charles F. Van Loan's classic is an essential reference for computational scientists and engineers;

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Adaptive Machine Learning Algorithms with Python

these problems, and create new algorithms for your own use. Authors Chanchal Chatterjee and Vwani P. Roychowdhury begin by introducing a common;

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Modern Anti-windup Synthesis

This book provides a wide variety of state-space--based numerical algorithms for the synthesis of feedback algorithms for linear systems;

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High-Performance Structural Fibers for Advanced Polymer Matrix Composites

Military use of advanced polymer matrix composites (PMC)a consisting of a resin matrix reinforced by high-performance carbon or organic;

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Numerical Linear Algebra for High-Performance Computers

scale eigenvalue problems on high-performance computers, and provides a rapid introduction to the world of vector and parallel processing for;

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Optimization Algorithms on Matrix Manifolds

existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers;

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Applied Parallel and Scientific Computing

, simulations of atomic scale systems, tools and environments for accelerator based computational biomedicine, GPU computing, high performance computing;

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High-Performance Algorithms for Mass Spectrometry-Based Omics

. Mass spectrometry is a diverse and versatile technology for high-throughput functional characterization of proteins, small molecules and;

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Structured Matrices

collects a set of contributions in structured matrix computations that covers different facets of the problems involved in this research area. The;

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High Performance Heterogeneous Computing

valuable'reference for researchers and practitioners in the area of high performance heterogeneous computing. It also serves as an excellent supplemental;

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