Описание: The text here provides the reader with an in-depth overview and analysis of the fundamental methods and techniques developed following G. Voronoi`s ground-breaking ideas, in the context of the vast and increasingly growing area of computational intelligence.
Описание: The text here provides the reader with an in-depth overview and analysis of the fundamental methods and techniques developed following G. Voronoi`s ground-breaking ideas, in the context of the vast and increasingly growing area of computational intelligence.
A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field
This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided.
The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution.
Presented in three parts--Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics--Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.
Описание: Computational Electrodynamics is a vast research field with a wide variety of tools. In physics the principle of gauge invariance plays a pivotal role as a guide towards a sensible formulation of the laws of nature as well as computing the properties of elementary particles using the lattice formulation of gauge theories, yet the gauge principle has played a much less pronounced role in performing computation in classical electrodynamics. In this work the author will demonstrate that starting from the gauge formulation of electrodynamics using the electromagnetic potentials leads to computational tools that can very well compete with the conventional electromagnetic field-based tools. Once accepting the formulation based on gauge fields, the computational code is very transparent due to the mimetic mapping of the electrodynamic variables on the computational grid. Although the illustrations and applications originate from microelectronic engineering, the method has a much larger range of applicability. Therefore this book is of interest to everyone having interest in computational electrodynamics. The volume is organized as follows: In part 1, a detailed introduction and overview is presented of the Maxwell equations as well as the derivation of the current and charge densities is different materials. Semiconductors are responding to electromagnetic fields in a non-linear way and the induced complications are discussed in detail. In part 2, the transition of the theory of electrodynamics, using the gauge potentials, to a formulation that can serve as the gateway to computational code is presented. In part 3, the feasibility and success of the methods of part 2 are demonstrated by a collection of microelectronic device designs. Part 4 focuses on a set of topical themes that brings the reader to the frontier of research in building the simulation tools using the gauge principle in computational electrodynamics.Technical topics discussed in the book include:Electromagnetic Field EquationsConstitutive RelationsDiscretization and Numerical AnalysisFinite Element and Finite Volume MethodsDesign of Integrated Passive Components.
Автор: Aboul-Ella Hassanien; Ajith Abraham; Francisco Her Название: Foundations of Computational Intelligence Volume 2 ISBN: 3642101836 ISBN-13(EAN): 9783642101830 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume is a reference work on the foundations of Computational Intelligence. It includes an overview chapter providing up-to-date and state-of-the research on the applications of Computational Intelligence techniques for approximation reasoning.
Автор: Nicolis Gregoire Название: Foundations of Complex Systems ISBN: 9814366609 ISBN-13(EAN): 9789814366601 Издательство: World Scientific Publishing Цена: 16632.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a self-contained presentation of the physical and mathematical laws governing complex systems. Complex systems arising in natural, engineering, environmental, life and social sciences are approached from a unifying point of view using an array of methodologies such as microscopic and macroscopic level formulations, deterministic and probabilistic tools, modeling and simulation. The book can be used as a textbook by graduate students, researchers and teachers in science, as well as non-experts who wish to have an overview of one of the most open, markedly interdisciplinary and fast-growing branches of present-day science.
Автор: Ajith Abraham; Aboul-Ella Hassanien; Andr? Ponce d Название: Foundations of Computational Intelligence ISBN: 3642101666 ISBN-13(EAN): 9783642101663 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computing techniques inspired by biological elements such as nervous systems, immune systems and genetics have been used in data mining. This book, one of a series on the foundations of Computational Intelligence, is focused on bio-inspired data mining.
Автор: Ajith Abraham; Aboul-Ella Hassanien; Patrick Siarr Название: Foundations of Computational Intelligence Volume 3 ISBN: 3642101658 ISBN-13(EAN): 9783642101656 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The wide use of global optimization applications has gained the attention of practitioners and researchers from numerous scientific fields. This book, one of a series on the foundations of Computational Intelligence, is focused on global optimization.
Автор: Ajith Abraham; Aboul-Ella Hassanien; Vaclav Sn??el Название: Foundations of Computational Intelligence Volume 5 ISBN: 3642424392 ISBN-13(EAN): 9783642424397 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This edited volume comprises 14 chapters, including several overview chapters, which provide up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. This is the fifth volume in the series.
Автор: Ajith Abraham; Aboul-Ella Hassanien; Andr? Ponce d Название: Foundations of Computational Intelligence ISBN: 3642101674 ISBN-13(EAN): 9783642101670 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computational tools or solutions based on intelligent systems are being used effectively in data mining applications. This book, one of a series on the foundations of Computational Intelligence, is focused on applications of techniques for data mining.
Описание: This book covers a broad spectrum of results in logic and set theory relevant to the foundations, as well as, the results in computational complexity and the interdisciplinary area of proof complexity. It presents the ideas behind the theoretical concepts.
Автор: Chi Tat Chong, Liang Yu Название: Recursion Theory: Computational Aspects of Definability ISBN: 3110275554 ISBN-13(EAN): 9783110275551 Издательство: Walter de Gruyter Цена: 20712.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph presents recursion theory from a generalized point of view centered on the computational aspects of definability. A major theme is the study of the structures of degrees arising from two key notions of reducibility, the Turing degrees and the hyperdegrees, using techniques and ideas from recursion theory, hyperarithmetic theory, and descriptive set theory.The emphasis is on the interplay between recursion theory and set theory, anchored on the notion of definability. The monograph covers a number of fundamental results in hyperarithmetic theory as well as some recent results on the structure theory of Turing and hyperdegrees. It also features a chapter on the applications of these investigations to higher randomness.
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