Introduction to Algorithms

A comprehensive and current introduction to the fundamentals of regression analysisIntroduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book.The new edition focuses on four key areas of improvement over the fifth edition: New exercises and data setsNew material on generalized regression techniquesThe inclusion of JMP software in key areasCarefully condensing the text where possibleIntroduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today's cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-b

This two-volume text provides a complete overview of the theory of Banach spaces, emphasising its interplay with classical and harmonic analysis (particularly Sidon sets) and probability. The authors give a full exposition of all results, as well as numerous exercises and comments to complement the text and aid graduate students in functional analysis. The book will also be an invaluable reference volume for researchers in analysis. Volume 1 covers the basics of Banach space theory, operatory theory in Banach spaces, harmonic analysis and probability. The authors also provide an annex devoted to compact Abelian groups. Volume 2 focuses on applications of the tools presented in the first volume, including Dvoretzky's theorem, spaces without the approximation property, Gaussian processes, and more. In volume 2, four leading experts also provide surveys outlining major developments in the field since the publication of the original French edition.

Introductory textbook in the important area of network security for undergraduate and graduate students‧ Comprehensively covers fundamental concepts with newer topics such as electronic cash, bit-coin

The Nobel Laureate discusses not only how and why he became a philosopher but also his conception of philosophy as a field distinct from science and literature. A source of inspiration for physicists

Explores concept of probability, surveys rules for addition and multiplication of probabilities, conditional probability, total probability, Bayes formula, Bernoulli's scheme, random variables, the C

A proposal that we think about digital technologies such as machine learning not in terms of artificial intelligence but as artificial communication.Algorithms that work with deep learning and big data are getting so much better at doing so many things that it makes us uncomfortable. How can a device know what our favorite songs are, or what we should write in an email? Have machines become too smart? In Artificial Communication, Elena Esposito argues that drawing this sort of analogy between algorithms and human intelligence is misleading. If machines contribute to social intelligence, it will not be because they have learned how to think like us but because we have learned how to communicate with them. Esposito proposes that we think of “smart” machines not in terms of artificial intelligence but in terms of artificial communication.To do this, we need a concept of communication that can take into account the possibility that a communication partner may be not a human being but an al

A new edition of the essential text and professional reference, with substantial newmaterial on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-baseflow.

The story of western painting – from Ancient Egyptian tomb decorations to modern art – told clearly and simply and published in association with The National Gallery.Beautifully illustrated with over

Introduction to Bioinformatics provides friendly guidance and advice on how to use a range of computational methods and techniques for retrieving and analysing biological data. The book is ideal for t

The second edition of Introduction to Mineralogy follows the highly successful first edition, which become an overnight market leader. Introduction to Mineralogy consolidates much of the material now

Introduction to Bioethics is a comprehensive introduction to the broad field of bioethics, focusing on key issues directly relevant to students of modern biological and medical sciences. Ethical issue

Introduction to Bioethics is a comprehensive introduction to the broad field of bioethics, focusing on key issues directly relevant to students of modern biological and medical sciences. Ethical issue

Essential IT Skills for On-the-Job SuccessMike Meyers, one of the premier computer and network skills trainers, has developed a learning system designed to teach key IT principles in an easy-to-unders

This groundbreaking text achieves what no other previous introduction to criminology text has achieved: it breaks down the myths and stereotypes that students have formed and has them critically exami

Introduction to Polymers, Second Edition discusses the synthesis, characterization, structure, and mechanical properties of polymers in a single text, giving approximately equal emphasis to each of th

This text offers a comprehensive and coherentintroduction to the fundamental topics of graph theory.It includes basic algorithms and emphasizes theunderstanding and writing of proofs about graphs.Thou

"In Introduction to Representation, Bonnie Ennis and Kimberly Witeck share ways to help students use algorithms, graphs, manipulatives, diagrams, and other written and pictorial forms to express mathe

This introduction to direction-of-arrival (DOA) estimation provides an overview and performance analysis of basic DOA algorithms and comparisons among themselves. It is intended for readers new to the

Now with updated ACLS algorithms An Introduction to Clinical Emergency Medicine is a much-needed resource for individuals practicing in this challenging field. It takes a novel approach, describing in

Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistic