Описание: Suitable for physicists, applied mathematicians, computer scientists, and engineers, this book presents introductory materials, similar to that on the PAMIR website. It also offers details on the use of the programs than is on the website.
Автор: Paul Fieguth Название: Statistical Image Processing and Multidimensional Modeling ISBN: 1461427053 ISBN-13(EAN): 9781461427056 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media).
Автор: Weirich Paul Название: Decision Space: Multidimensional Utility Analysis ISBN: 0521800099 ISBN-13(EAN): 9780521800099 Издательство: Cambridge Academ Цена: 15206.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In Decision Space: Multidimensional Utility Analysis, first published in 2001, Paul Weirich increases the power and versatility of utility analysis and in the process advances decision theory. Combining traditional and novel methods of option evaluation into one systematic method, multidimensional utility analysis is a valuable tool in decision theory.
Автор: Nishisato, Shizuhiko Название: Multidimensional Nonlinear Descriptive Analysis ISBN: 0367390647 ISBN-13(EAN): 9780367390648 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Поставка под заказ.
Описание:
Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations.
This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data analysis in subsequent chapters. The next two parts contain applications of MUNDA to diverse data types, with each chapter devoted to one type of categorical data, a brief historical comment, and basic skills peculiar to the data types. The final part examines several problems and then concludes with suggestions for future progress.
Covering both the early and later years of MUNDA research in the social sciences, psychology, ecology, biology, and statistics, this book provides a framework for potential developments in even more areas of study.
Описание: Suitable for physicists, applied mathematicians, computer scientists, and engineers, this book presents introductory materials, similar to that on the PAMIR website. It also offers details on the use of the programs than is on the website.
Автор: Achille A. Lemmi; Gianni Betti Название: Fuzzy Set Approach to Multidimensional Poverty Measurement ISBN: 1441941711 ISBN-13(EAN): 9781441941718 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume brings together advanced thinking on the multidimensional measurement of poverty.
Описание: This work considers Kronecker-based models with finite as well as countably infinite state spaces for multidimensional Markovian systems by paying particular attention to those whose reachable state spaces are smaller than their product state spaces. Numerical methods for steady-state and transient analysis of Kronecker-based multidimensional Markovian models are discussed in detail together with implementation issues. Case studies are provided to explain concepts and motivate use of methods. Having grown out of research from the past twenty years, this book expands upon the author’s previously published book Analyzing Markov Chains using Kronecker Products (Springer, 2012). The subject matter is interdisciplinary and at the intersection of applied mathematics and computer science. The book will be of use to researchers and graduate students with an understanding of basic linear algebra, probability, and discrete mathematics.
Автор: George W. Hart Название: Multidimensional Analysis ISBN: 0387944176 ISBN-13(EAN): 9780387944173 Издательство: Springer Рейтинг: Цена: 10475.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Das Buch behandelt die mathematischen Eigenschaften dimensionsbehafteter Grossen wie Lange, Potentialdifferenz und Viskositat. Nach einer sorgfaltigen Untersuchung des Messprozesses und der aus ihm zu erwartenden numerischen Ergebnisse konstruiert der Autor streng den Begriff der dimensionsbehafteten Zahl und diskutiert ihre algebraische Struktur.
Автор: I. Borg; J. Lingoes Название: Multidimensional Similarity Structure Analysis ISBN: 146129147X ISBN-13(EAN): 9781461291473 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Multidimensional Similarity Structure Analysis comprises a class of models that represent similarity among entities (for example, variables, items, objects, persons, etc.) in multidimensional space to permit one to grasp more easily the interrelations and patterns present in the data.
Описание: The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Автор: N.K. Bose Название: Multidimensional Systems Theory ISBN: 9027717648 ISBN-13(EAN): 9789027717641 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Approach your problem from the right end It isn't that they can't see the solution. and begin with the answers. It is that they can't see the problem. Then one day, perhaps you will find the final question. G. K. Chesterton. The Scandal of Father Brown The point of a Pin. The Hermit Clad in Crane Feathers in R. van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of mono- graphs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addi- tion to this there are such new emerging subdisciplines as "experimental mathematical", "CFD", "completely integrable systems", "chaos, synergetics and large-scale order", which are almost impossible to fit into the existing classification schemes.
Автор: Jacob Kogan; Charles Nicholas; Marc Teboulle Название: Grouping Multidimensional Data ISBN: 3642066542 ISBN-13(EAN): 9783642066542 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data.
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