Algorithms

Written in easy to understand language, this self-explanatory guide introduces the fundamentals of finite element methods and its application to differential equations. Beginning with a brief introduction to Sobolev spaces and elliptic scalar problems, the text progresses through an explanation of finite element spaces and estimates for the interpolation error. The concepts of finite element methods for parabolic scalar parabolic problems, object-oriented finite element algorithms, efficient implementation techniques, and high dimensional parabolic problems are presented in different chapters. Recent advances in finite element methods, including non-conforming finite elements for boundary value problems of higher order and approaches for solving differential equations in high dimensional domains are explained for the benefit of the reader. Numerous solved examples and mathematical theorems are interspersed throughout the text for enhanced learning.

Thisbook offers a comprehensive introduction to polymer rheology with a focus onthe viscoelastic characterization of polymeric materials. It contains variousnumerical algorithms for the processing of

Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and re

This dynamic reference work provides solutions to vital algorithmic problems for scholars, researchers, practitioners, teachers and students in fields such as computer science, mathematics, statistics

Algorithms for Automating Open Source Intelligence (OSINT) presents information on the gathering of information and extraction of actionable intelligence from openly available sources, including news

In this work we plan to revise the main techniques for enumeration algorithms and to show four examples of enumeration algorithms that can be applied to efficiently deal with some biological problems

Based on the authors’ market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Struct

Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduct

Equip yourself for success with a state-of-the-art approach to algorithms available only in Miller/Boxer's ALGORITHMS SEQUENTIAL AND PARALLEL: A UNIFIED APPROACH, 3E. This unique and functional text g

The meta-heuristic hybrid optimization techniques discussed in this collection address the intrinsic difficulty of algorithms and the need to model uncertainty problems troubling modern industrial, bu

The 21 papers in this collection develop new algorithms for helping machines learn from previous data and describe the application of machine learning algorithms to image retrieval, computer vision, h

This book constitutes the refereed proceedings of the 6th International Conference, FUN 2012, held in June 2012 in Venice, Italy. The 34 revised full papers were carefully reviewed and selected from 5

Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web.

This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis o

A textbook for postgraduate students and industry professionals.

For many years Esko Ukkonen has played a major role in the advancement of computer science in Finland. He was the key person in the development of the school of algorithmic research and has contribute

A culmination of the authors' years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational dat

Extensive amounts of operational data are generated over time by the health monitoring system of a structure’s management system, yet there are few analysis algorithms which can tell the exact w

First published in 1993, this thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members? What general methods are useful for listing combinatorial structures? How can these be applied to those families which are of interest to theoretical computer scientists and combinatorialists? Amongst those families considered are unlabelled graphs, first order one properties, Hamiltonian graphs, graphs with cliques of specified order, and k-colourable graphs. Some related work is also included, which compares the listing problem with the difficulty of solving the existence problem, the construction problem, the random sampling problem, and the counting problem. In particular, the difficulty of evaluating Pólya's cycle polynomial is demonstrated.

New perspective technologies of genetic search and evolution simulation represent the kernel of this book. The authors wanted to show how these technologies are used for practical problems solution. T

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its imp

Using mathematical tools from number theory and finite fields, Applied Algebra: Codes, Ciphers, and Discrete Algorithms, Second Edition presents practical methods for solving problems in data security

Focusing on grid computing and asynchronism, Parallel Iterative Algorithms explores the theoretical and practical aspects of parallel numerical algorithms. Each chapter contains a theoretical discussi

Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have n

Algorithms that have to process large data sets have to take into account that the cost of memory access depends on where the data is stored. Traditional algorithm design is based on the von Neumann m

First published in 1985, this book presents background material, descriptions, and supporting theory relating to practical numerical algorithms for the solution of huge eigenvalue problems. It continu

This volume is devoted to Analysis of Algorithms, a field that Knuth founded and still considers his main life's work.

This college textbook introduces algorithms for solving real problems that arise frequently in computer applications, basic principles of computational complexity, and NP -completeness and parallel a

"Mathematical Methods and Algorithms for Signal Processing" tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Build