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Author: Anna M. Bigatti
Publisher: Springer
ISBN: 364238742X
Category : Mathematics
Languages : en
Pages : 201
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Book Description
This work covers three important aspects of monomials ideals in the three chapters "Stanley decompositions" by Jürgen Herzog, "Edge ideals" by Adam Van Tuyl and "Local cohomology" by Josep Álvarez Montaner. The chapters, written by top experts, include computer tutorials that emphasize the computational aspects of the respective areas. Monomial ideals and algebras are, in a sense, among the simplest structures in commutative algebra and the main objects of combinatorial commutative algebra. Also, they are of major importance for at least three reasons. Firstly, Gröbner basis theory allows us to treat certain problems on general polynomial ideals by means of monomial ideals. Secondly, the combinatorial structure of monomial ideals connects them to other combinatorial structures and allows us to solve problems on both sides of this correspondence using the techniques of each of the respective areas. And thirdly, the combinatorial nature of monomial ideals also makes them particularly well suited to the development of algorithms to work with them and then generate algorithms for more general structures.
Author: Anna M. Bigatti
Publisher: Springer
ISBN: 364238742X
Category : Mathematics
Languages : en
Pages : 201
Get Book Here
Book Description
This work covers three important aspects of monomials ideals in the three chapters "Stanley decompositions" by Jürgen Herzog, "Edge ideals" by Adam Van Tuyl and "Local cohomology" by Josep Álvarez Montaner. The chapters, written by top experts, include computer tutorials that emphasize the computational aspects of the respective areas. Monomial ideals and algebras are, in a sense, among the simplest structures in commutative algebra and the main objects of combinatorial commutative algebra. Also, they are of major importance for at least three reasons. Firstly, Gröbner basis theory allows us to treat certain problems on general polynomial ideals by means of monomial ideals. Secondly, the combinatorial structure of monomial ideals connects them to other combinatorial structures and allows us to solve problems on both sides of this correspondence using the techniques of each of the respective areas. And thirdly, the combinatorial nature of monomial ideals also makes them particularly well suited to the development of algorithms to work with them and then generate algorithms for more general structures.
Author: Hal R. Varian
Publisher: Springer Science & Business Media
ISBN: 9780387945187
Category : Business & Economics
Languages : en
Pages : 486
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Book Description
This collection of articles is edited by Hal Varian, Dean of the School of Information Management and Systems, University of California, Berkeley. It provides a high quality and practical selection of contributed articles that impart the expertise of an international contingent of Mathematica users from the economic, financial, investments, quantitative business and operations research communities.
Author: American Society for Testing and Materials
Publisher: ASTM International
ISBN:
Category : Infrared spectra
Languages : en
Pages : 119
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Book Description
Author: Matthias Dehmer
Publisher: John Wiley & Sons
ISBN: 3527694374
Category : Medical
Languages : en
Pages : 368
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Book Description
This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.
Author: Thomas Trappenberg
Publisher: Oxford University Press
ISBN: 0192869361
Category : Medical
Languages : en
Pages : 411
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Book Description
Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the complexity of the field, and its increasing importance in progressing our understanding of how the brain works, there has long been a need for an introductory text on what is often assumed to be an impenetrable topic. The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the previous editions. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental network architectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can be gained with such studies. Each chapter starts by introducing its topic with experimental facts and conceptual questions related to the study of brain function. An additional feature is the inclusion of simple Matlab programs that can be used to explore many of the mechanisms explained in the book. An accompanying webpage includes programs for download. The book will be the essential text for anyone in the brain sciences who wants to get to grips with this topic.
Author: Gareth James
Publisher: Springer Science & Business Media
ISBN: 1461471389
Category : Mathematics
Languages : en
Pages : 434
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Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Author: Dennis G. Zill
Publisher: Jones & Bartlett Learning
ISBN: 1284206246
Category : Mathematics
Languages : en
Pages : 1065
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Book Description
This package includes the printed hardcover book and access to the Navigate 2 Companion Website. The seventh edition of Advanced Engineering Mathematics provides learners with a modern and comprehensive compendium of topics that are most often covered in courses in engineering mathematics, and is extremely flexible to meet the unique needs of courses ranging from ordinary differential equations, to vector calculus, to partial differential equations. Acclaimed author, Dennis G. Zill's accessible writing style and strong pedagogical aids, guide students through difficult concepts with thoughtful explanations, clear examples, interesting applications, and contributed project problems.
Author: Basabdatta Sen Bhattacharya
Publisher: Springer
ISBN: 3319200372
Category : Medical
Languages : en
Pages : 329
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Book Description
This book is a collection of articles by leading researchers working at the cutting edge of neuro-computational modelling of neurological and psychiatric disorders. Each article contains model validation techniques used in the context of the specific problem being studied. Validation is essential for neuro-inspired computational models to become useful tools in the understanding and treatment of disease conditions. Currently, the immense diversity in neuro-computational modelling approaches for investigating brain diseases has created the need for a structured and coordinated approach to benchmark and standardise validation methods and techniques in this field of research. This book serves as a step towards a systematic approach to validation of neuro-computational models used for studying brain diseases and should be useful for all neuro-computational modellers.
Author: Jörg Arndt
Publisher: Springer Science & Business Media
ISBN: 364214764X
Category : Computers
Languages : en
Pages : 980
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Book Description
This book provides algorithms and ideas for computationalists. Subjects treated include low-level algorithms, bit wizardry, combinatorial generation, fast transforms like the Fourier transform, and fast arithmetic for both real numbers and finite fields. Various optimization techniques are described and the actual performance of many given implementations is examined. The focus is on material that does not usually appear in textbooks on algorithms. The implementations are done in C++ and the GP language, written for POSIX-compliant platforms such as the Linux and BSD operating systems.
Author: C. A. Brebbia
Publisher: WIT Press
ISBN: 1845640314
Category : Technology & Engineering
Languages : en
Pages : 369
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Book Description
Bringing together the work of practitioners in many fields of engineering, materials and computational science, this book includes most of the papers presented at the Second International Conference on Material Characterisation. Compiled with the central aim of encouraging interaction between experimentalists and modelers, the contributions featured are divided under the following sections: MICROSTRUCTURES ? Composites; Alloys; Ceramics; Cements; Foams; Suspensions; Biomaterials; Thin Films; Coatings. EXPERIMENTAL METHODS - Optical Imaging; SEM, TEM; X-Ray Microtomography; Ultrasonic Techniques; NMR/MRI; Micro/Nano Indentation; Thermal Analysis; Surface Chemistry. COMPUTATIONAL METHODS - Continuum Methods (FEM, FV, BEM); Particle Models (MD, DPD, Lattice-Boltzmann); Montecarlo Methods; Cellular Automata; Hybrid Multiscale Methods; and Damage Mechanics.
