Showing results for "Computational Methods for General Sparse Matrices German"

The subject of sparse matrices has its root in such diverse fields as management science, power systems analysis, surveying, circuit theory, and structural analysis. Efficient use of sparsity is a key to solving large problems in many fields. This second edition is a complete rewrite of the first edition published 30 years ago. Much has changed since that time. Problems have grown greatly in size and complexity; nearly all examples in the first edition were of order less than 5,000 in the ...

This book provides a concise description of a variety of simulation methods to model soft matter with a particular focus on polymeric systems. Along with the fundamental concepts of the theory behind the methods, a comprehensive set of examples taken from the broad pool of soft materials is included. These exemplify how, thanks to the increased computational resources nowadays available to almost any research group, computational methods have become a powerful tool to sit alongside other e...

Matrices may seem like abstract mathematical concepts, but they play an important role in many sectors and have particularly notable applications in business. By matrices I mean matrix charts, matrix data analysis and matrix calculations, which enable efficient management and visualization of multivariate data, which is a common requirement in business activities and management practice.From strategy planning, inventory management, financial analysis to market research, matrices ha...

Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis model relies heavily on appropriate hyper-parameters. However, most hyper-parameters are data-dependent, and using grid-search to tune these hyper-parameters is truly laborious and expensive in computational terms. Hence, how to achieve efficient ...

The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis.Features:Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically...

This second edition of a well-received book presents new perspectives on modern nanoscale problems, where fundamental science meets technology and computer modeling. Along with traditional computational techniques such as finite-difference schemes, finite element analysis and Ewald summation, the book describes a new finite-difference calculus of Flexible Local Approximation MEthods (FLAME), which qualitatively improves the numerical accuracy in a variety of problems. Application areas in ...

A textbook for a one-semester course in linear algebra for graduate or upper-level undergraduate students of mathematics and engineering. Employs a matrix perspective, and emphasizes training in definitions, theorems, and proofs. Annotation copyright Book News, Inc. Portland, Or.

Chemical vapor sensing arrays have grown in popularity over the past two decades, finding applications for tasks such as process control, environmental monitoring, and medical diagnosis. This is the first in-depth analysis of the process of choosing materials and components for these "electronic noses", with special emphasis on computational methods. For a view of component selection with an experimental perspective, readers may refer to the complementary volume of Integrated Microanal...

Computational Methods for Communication Science showcases the use of innovative computational methods in the study of communication.This book discusses the validity of using big data in communication science and showcases a number of new methods and applications in the fields of text and network analysis. Computational methods have the potential to greatly enhance the scientific study of communication because they allow us to move towards collaborative large-N studies of a...

Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different cha...

The book offers a practice-oriented introduction to the mathematical methods of electrical engineering. The focus is on the solution of ordinary and partial differential equations using analytical and numerical methods. The analytical methods are opposed to the numerical methods. The differential equations were chosen with a view to the problems of electrical engineering. It is shown how they can also be transferred to mechanics or thermodynamics. Numerous examples and exercises with elabo...

This volume contains the best papers presented at the 2nd ECCOMAS International Conference on Multiscale Computations for Solids and Fluids, held June 10-12, 2015.Topics dealt with include multiscale strategy for efficient development of scientific software for large-scale computations, coupled probability-nonlinear-mechanics problems and solution methods, and modern mathematical and computational setting for multi-phase flows and fluid-structure interaction.The papers cons...