Anisotropy Across Fields and Scales

Anisotropy Across Fields and Scales PDF Author: Evren Özarslan
Publisher: Springer Nature
ISBN: 3030562158
Category : Algebra
Languages : en
Pages : 284

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Book Description
This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain. The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas. This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28-November 2, 2018.

Anisotropy Across Fields and Scales

Anisotropy Across Fields and Scales PDF Author: Evren Özarslan
Publisher: Springer Nature
ISBN: 3030562158
Category : Algebra
Languages : en
Pages : 284

Get Book Here

Book Description
This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain. The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas. This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28-November 2, 2018.

Learning from Data Streams

Learning from Data Streams PDF Author: João Gama
Publisher: Springer Science & Business Media
ISBN: 3540736794
Category : Computers
Languages : en
Pages : 244

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Book Description
Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Tensor Networks for Dimensionality Reduction and Large-scale Optimization

Tensor Networks for Dimensionality Reduction and Large-scale Optimization PDF Author: Andrzej Cichocki
Publisher:
ISBN: 9781680832235
Category : Dimension reduction (Statistics)
Languages : en
Pages : 180

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Book Description
Modern applications in engineering and data science are increasingly based on multidimensional data of exceedingly high volume, variety, and structural richness. However, standard machine learning algorithms typically scale exponentially with data volume and complexity of cross-modal couplings - the so called curse of dimensionality - which is prohibitive to the analysis of large-scale, multi-modal and multi-relational datasets. Given that such data are often efficiently represented as multiway arrays or tensors, it is therefore timely and valuable for the multidisciplinary machine learning and data analytic communities to review low-rank tensor decompositions and tensor networks as emerging tools for dimensionality reduction and large scale optimization problems. Our particular emphasis is on elucidating that, by virtue of the underlying low-rank approximations, tensor networks have the ability to alleviate the curse of dimensionality in a number of applied areas. In Part 1 of this monograph we provide innovative solutions to low-rank tensor network decompositions and easy to interpret graphical representations of the mathematical operations on tensor networks. Such a conceptual insight allows for seamless migration of ideas from the flat-view matrices to tensor network operations and vice versa, and provides a platform for further developments, practical applications, and non-Euclidean extensions. It also permits the introduction of various tensor network operations without an explicit notion of mathematical expressions, which may be beneficial for many research communities that do not directly rely on multilinear algebra. Our focus is on the Tucker and tensor train (TT) decompositions and their extensions, and on demonstrating the ability of tensor networks to provide linearly or even super-linearly (e.g., logarithmically) scalable solutions, as illustrated in detail in Part 2 of this monograph.

From Algebraic Structures to Tensors

From Algebraic Structures to Tensors PDF Author: Gérard Favier
Publisher: John Wiley & Sons
ISBN: 1786301547
Category : Technology & Engineering
Languages : en
Pages : 324

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Book Description
Nowadays, tensors play a central role for the representation, mining, analysis, and fusion of multidimensional, multimodal, and heterogeneous big data in numerous fields. This set on Matrices and Tensors in Signal Processing aims at giving a self-contained and comprehensive presentation of various concepts and methods, starting from fundamental algebraic structures to advanced tensor-based applications, including recently developed tensor models and efficient algorithms for dimensionality reduction and parameter estimation. Although its title suggests an orientation towards signal processing, the results presented in this set will also be of use to readers interested in other disciplines. This first book provides an introduction to matrices and tensors of higher-order based on the structures of vector space and tensor space. Some standard algebraic structures are first described, with a focus on the hilbertian approach for signal representation, and function approximation based on Fourier series and orthogonal polynomial series. Matrices and hypermatrices associated with linear, bilinear and multilinear maps are more particularly studied. Some basic results are presented for block matrices. The notions of decomposition, rank, eigenvalue, singular value, and unfolding of a tensor are introduced, by emphasizing similarities and differences between matrices and tensors of higher-order.

Measurement With Persons

Measurement With Persons PDF Author: Birgitta Berglund
Publisher: Psychology Press
ISBN: 1136723749
Category : Psychology
Languages : en
Pages : 423

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Book Description
Measurements with persons are those in which human perception and interpretation are used for measuring complex, holistic quantities and qualities, which are perceived by the human brain and mind. Providing means for reproducible measurement of parameters such as pleasure and pain has important implications in evaluating all kind of products, services, and conditions. This book inaugurates a new era for this subject: a multi- and inter-disciplinary volume in which world-renowned scientists from the psychological, physical, biological, and social sciences reach a common understanding of measurement theory and methods. In the first section, generic theoretical and methodological issues are treated, including the conceptual basis of measurement in the various fields involved; the development of formal, representational, and probabilistic theories; the approach to experimentation; and the theories, models, and methods for multidimensional problems. In the second section, several implementation areas are presented, including sound, visual, skin, and odor perception, functional brain imagining, body language and emotions, and, finally, the use of measurements in decision making Measurement with Persons will appeal to a wide audience across a range of sciences, including general psychology and psychophysics, measurement theory, metrology and instrumentation, neurophysiology, engineering, biology, and chemistry.

Tensors for Data Processing

Tensors for Data Processing PDF Author: Yipeng Liu
Publisher: Academic Press
ISBN: 0323859658
Category : Technology & Engineering
Languages : en
Pages : 598

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Book Description
Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods. As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry. - Provides a complete reference on classical and state-of-the-art tensor-based methods for data processing - Includes a wide range of applications from different disciplines - Gives guidance for their application

Mathematics of Multidimensional Fourier Transform Algorithms

Mathematics of Multidimensional Fourier Transform Algorithms PDF Author: Richard Tolimieri
Publisher: Springer Science & Business Media
ISBN: 1468402056
Category : Technology & Engineering
Languages : en
Pages : 241

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Book Description
The main emphasis of this book is the development of algorithms for processing multi-dimensional digital signals, and particularly algorithms for multi-dimensional Fourier transforms, in a form that is convenient for writing highly efficient code on a variety of vector and parallel computers.

Evolutionary Biology of Ostracoda

Evolutionary Biology of Ostracoda PDF Author: N. Ikeya
Publisher: Elsevier
ISBN: 0080868525
Category : Science
Languages : en
Pages : 1373

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Book Description
There are many competitive works on the market concerning evolutionary biology, but this volume is quite distinctive in its idiographic aspect focusing on Ostracoda viewed from a wide range of disciplines, ages and environments. The book deals with various lines of idiographic biology and palaeontology of Ostracoda and nomothetic trials focusing strongly on evolutionary biology. Particular themes are morphology, biology, evolution, speciation, ecology, palaeoecology, deep sea fauna, biogeography, palaeobiogeography, biostratigraphy and exploration, all concerning Ostracoda.The last decade has witnessed a spectacular renewal of interest in the study of Otracoda, particularly in the evolutionary biology of Ostracoda, including speciation. Ostracoda are unique, ranging in age from the Cambrian period to modern times with carapaces ready to be preserved as fossils, providing various lines of invaluable evidence regarding evolutionary processes.More than 120 participants from 20 countries assembled at the Ninth International Symposium on Ostracoda and this book is a collection of all the papers presented at the Symposium, plus selected papers submitted by non-attending members. It presents an outstanding record of much pioneering research and will be of interest to specalists in Ostracoda as well as all earth and life scientists concerned with evolution. Its value is further enhanced by easy-to-use indexes of authors, localities and taxa.

Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases PDF Author: Toon Calders
Publisher: Springer
ISBN: 3662448483
Category : Computers
Languages : en
Pages : 749

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Book Description
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

Statistical Shape Analysis

Statistical Shape Analysis PDF Author: Ian L. Dryden
Publisher: John Wiley & Sons
ISBN: 1119072514
Category : Mathematics
Languages : en
Pages : 496

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Book Description
A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while retaining sufficient detail for more specialist statisticians to appreciate the challenges and opportunities of this new field. Computer code has been included for instructional use, along with exercises to enable readers to implement the applications themselves in R and to follow the key ideas by hands-on analysis. Statistical Shape Analysis: with Applications in R will offer a valuable introduction to this fast-moving research area for statisticians and other applied scientists working in diverse areas, including archaeology, bioinformatics, biology, chemistry, computer science, medicine, morphometics and image analysis .