Author: Steve Y. Oudot
Publisher: American Mathematical Soc.
ISBN: 1470434431
Category : Mathematics
Languages : en
Pages : 229
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Book Description
Persistence theory emerged in the early 2000s as a new theory in the area of applied and computational topology. This book provides a broad and modern view of the subject, including its algebraic, topological, and algorithmic aspects. It also elaborates on applications in data analysis. The level of detail of the exposition has been set so as to keep a survey style, while providing sufficient insights into the proofs so the reader can understand the mechanisms at work. The book is organized into three parts. The first part is dedicated to the foundations of persistence and emphasizes its connection to quiver representation theory. The second part focuses on its connection to applications through a few selected topics. The third part provides perspectives for both the theory and its applications. The book can be used as a text for a course on applied topology or data analysis.
Author: Ervin Sejdic
Publisher: CRC Press
ISBN: 1351061216
Category : Medical
Languages : en
Pages : 1235
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Book Description
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
Author: Jerry L. Prince
Publisher: Springer
ISBN: 364202498X
Category : Computers
Languages : en
Pages : 744
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Book Description
This book constitutes the refeered proceedings of the 21st International Conference on Information Processing in Medical Imaging, IPMI 2009, held in Williamsburg, VA, USA, in July 2009 The 26 revised full papers and 33 revised poster papers presented were carefully reviewed and selected from 150 submissions. The papers are organized in topical sections on diffusion imaging, PET imaging, image registration, functional networks, space curves, tractography, microscopy, exploratory analyses, features and detection, image guided surgery, shape analysis, motion, and segmentation and validation.
Author: Moo K. Chung
Publisher: Cambridge University Press
ISBN: 110718486X
Category : Computers
Languages : en
Pages : 343
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Book Description
This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 810
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Book Description
Author: Moo K. Chung
Publisher: World Scientific
ISBN: 9814335444
Category : Computers
Languages : en
Pages : 424
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Book Description
Computational neuroanatomy is an emerging field that utilizes various non-invasive brain imaging modalities, such as MRI and DTI, in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations. This discipline emerged about twenty years ago and has made substantial progress in the past decade. The main goals of this book are to provide an overview of various mathematical, statistical and computational methodologies used in the field to a wide range of researchers and students, and to address important yet technically challenging topics in further detail.
Author: Herbert Edelsbrunner
Publisher: American Mathematical Society
ISBN: 1470467690
Category : Mathematics
Languages : en
Pages : 241
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Book Description
Combining concepts from topology and algorithms, this book delivers what its title promises: an introduction to the field of computational topology. Starting with motivating problems in both mathematics and computer science and building up from classic topics in geometric and algebraic topology, the third part of the text advances to persistent homology. This point of view is critically important in turning a mostly theoretical field of mathematics into one that is relevant to a multitude of disciplines in the sciences and engineering. The main approach is the discovery of topology through algorithms. The book is ideal for teaching a graduate or advanced undergraduate course in computational topology, as it develops all the background of both the mathematical and algorithmic aspects of the subject from first principles. Thus the text could serve equally well in a course taught in a mathematics department or computer science department.
Author: Gregory Bateson
Publisher: University of Chicago Press
ISBN: 9780226039053
Category : Medical
Languages : en
Pages : 572
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Book Description
Gregory Bateson was a philosopher, anthropologist, photographer, naturalist, and poet, as well as the husband and collaborator of Margaret Mead. This classic anthology of his major work includes a new Foreword by his daughter, Mary Katherine Bateson. 5 line drawings.
Author: Regula Burckhardt Qureshi
Publisher: Routledge
ISBN: 1136541357
Category : Music
Languages : en
Pages : 276
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Book Description
Well-known contributors analyze the ways in which Marxist thought enters into music discourse. Exploring everything from Marxism in hip-hop to feudal properties of Hindustani music to revolutionary music of Central America, the essays in this book find surprising, paradigm-shifting revelations. This book will revolutionize the way music production and consumption is viewed. First published in 2002.
Author: Ezra Miller
Publisher: Springer Science & Business Media
ISBN: 9780387237077
Category : Mathematics
Languages : en
Pages : 442
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Book Description
Recent developments are covered Contains over 100 figures and 250 exercises Includes complete proofs
