An extraordinary variety of disciplines rely on graphs to convey their fundamentals as well as their finer points. With this concise and well-written text, anyone with a firm grasp of general mathematics can follow the development of graph theory and learn to apply its principles in methods both formal and abstract. The work of a distinguished mathematician, this text uses practical examples to illustrate the theory's broad range of applications, from the behavioral sciences, information theory, cybernetics, and other areas, to mathematical disciplines such as set and matrix theory. 1966 edition. 109 black-and-white illus.

Widely acclaimed algebra text. This book is designed to give the reader insight into the power and beauty that accrues from a rich interplay between different areas of mathematics. The book carefully develops the theory of different algebraic structures, beginning from basic definitions to some in-depth results, using numerous examples and exercises to aid the reader's understanding. In this way, readers gain an appreciation for how mathematical structures and their interplay lead to powerful results and insights in a number of different settings.

During the past decade there has been an explosion in computation and information technology. With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book descibes theimprtant ideas in these areas ina common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a vluable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learing (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

In this stunning new book, Malcolm Gladwell takes us on an intellectual journey through the world of "outliers"—the best and the brightest, the most famous and the most successful. He asks the question: what makes high-achievers different? His answer is that we pay too much attention to what successful people are like, and too little attention to where they are from: that is, their culture, their family, their generation, and the idiosyncratic experiences of their upbringing. Along the way he explains the secrets of software billionaires, what it takes to be a great soccer player, why Asians are good at math, and what made the Beatles the greatest rock band.

Brilliant and entertaining, OUTLIERS is a landmark work that will simultaneously delight and illuminate.

On February 13, 2003, a plane carrying three American civilian contractors—Marc Gonsalves, Keith Stansell, and Tom Howes—crash-landed in the mountainous jungle of Colombia. Dazed and shaken, they emerged from the plane bloodied and injured as gunfire rained down around them. As of that moment they were prisoners of the FARC, a Colombian terrorist and Marxist rebel organization. In an instant they had become American captives in Colombia's volatile and ongoing conflict, which has lasted for almost fifty years.

In Out of Captivity, Gonsalves, Stansell, and Howes recount for the first time their amazing tale of survival, friendship, and, ultimately, rescue, tracing their five and a half years as hostages of the FARC. Their story takes you inside one of the world's most notorious terrorist organizations, going behind enemy lines with vivid and haunting imagery. Their words conjure a reality that few people have ever encountered—from sleeping on beds literally carved out of the jungle to escaping Colombian military air strikes under the cover of darkness to being bound with steel chains by their captors. Describing backbreaking starvation marches and forced isolation, the authors chronicle their confrontations and interactions with the FARC guerrilla soldiers—a motley crew of brainwashed, idealistic teenagers and seasoned vet-erans who've been around long enough to realize that the only way out of the FARC is in a body bag.

Though the physical punishments their bodies endured were unrelenting, the psychological battles they waged were the ultimate test of their resolve. With candid detail, Gonsalves, Stansell, and Howes relate the perilous mental struggles they each experienced, as they grappled with feelings of guilt, fear, and anxiety for the families and lives they'd left behind. Exposing the transformative power of captivity, they show how they turned these fears into strengths, using their memories and their families, their pasts and their futures, to motivate them in their quest for survival.

Despite the odds and the conditions, despite the chains and the silence, and despite the often tense relationships they experienced with their fellow Colombian hostages, they had one another, forging a bond that allowed them to cope with the horrific conditions of their confinement. This brotherhood enabled them to persevere through the worst that the FARC threw at them while always reminding them of their ultimate goal: freedom.

A harrowing account of one of the longest civilian hostage crises in United States history, Out of Captivity is a remarkable and compelling exploration of how far three Americans were willing to go as they fought to stay alive for themselves, their families, and one another.

A fresh approach to introductory topology, this volume explains nontrivial applications of metric space topology to analysis, clearly establishing their relationship. Also, topics from elementary algebraic topology focus on concrete results with minimal algebraic formalism. The first two chapters consider metric space and point-set topology; the second two, algebraic topological material. 1983 edition. Solutions to Selected Exercises. List of Notations. Index. 51 illus.

This book is based on notes from a course on set theory and metric spaces taught by Edwin Spanier, and also incorporates with his permission numerous exercises from those notes. The volume includes an Appendix that helps bridge the gap between metric and topological spaces, a Selected Bibliography, and an Index.

This text is geared towards a one-semester graduate-level course in statistical signal processing and estimation theory. The author balances technical detail with practical and implementation issues, delivering an exposition that is both theoretically rigorous and application-oriented. The book covers topics such as minimum variance unbiased estimators, the Cramer-Rao bound, best linear unbiased estimators, maximum likelihood estimation, recursive least squares, Bayesian estimation techniques, and the Wiener and Kalman filters. The author provides numerous examples, which illustrate both theory and applications for problems such as high-resolution spectral analysis, system identification, digital filter design, adaptive beamforming and noise cancellation, and tracking and localization. The primary audience will be those involved in the design and implementation of optimal estimation algorithms on digital computers. The text assumes that you have a background in probability and random processes and linear and matrix algebra and exposure to basic signal processing. Students as well as researchers and practicing engineers will find the text an invaluable introduction and resource for scalar and vector parameter estimation theory and a convenient reference for the design of successive parameter estimation algorithms.

An undergraduate introduction to the fundamentals of topology — engagingly written, filled with helpful insights, complete with many stimulating and imaginative exercises to help students develop a solid grasp of the subject.