How the West Grew Rich or Pattern Classification

How the West Grew Rich: The Economic Transformation of the Industrial World

Author: Nathan Rosenberg

How did the West—Europe, Canada, and the United States—escape from immemorial poverty into sustained economic growth and material well-being when other societies remained trapped in an endless cycle of birth, hunger, hardship, and death? In this elegant synthesis of economic history, two scholars argue that it is the political pluralism and the flexibility of the West’s institutions—not corporate organization and mass production technology—that explain its unparalleled wealth.

What People Are Saying

Jane Jacobs
"A lucid, well-reasoned antidote to false notions that prosperity has been built upon imperialism, exploitation, or legerdemain."

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Pattern Classification, Vol. 1

Author:

The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

SciTech Book News

...provides information needed to choose the most appropriate of the many available technique for a given class of problems.

SciTech Book News

...provides information needed to choose the most appropriate of the many available technique for a given class of problems.

Sargur N. Srihari

The first edition of this book, published 30 years ago by Duda and Hart, has been a defining book for the field of Pattern Recognition. Stork has done a superb job of updating the book. He has undertaken a monumental task of sifting through 30 years of material in a rapidly growing field and presented another snapshot of the field, determining what will be of importance for the next 30 years and incorporating it into this second edition. The style is easy to read as in the original book and the statistical, mathematical material comes alive with many new illustrations. The end result is harmonious, leading the reader through many new topics...

Booknews

Pattern recognition systems play a role in applications as diverse as speech recognition, optical character recognition, image processing, and signal analysis. This reference provides information needed to choose the most appropriate of the many available techniques for a given class of problems. The latest edition includes explanations of classical and new methods, including neural networks, stochastic methods, genetic algorithms, and theory of learning. It provides algorithms to explain specific pattern-recognition and learning techniques as well as appendices covering the necessary mathematical background. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Table of Contents:

Bayesian Decision Theory.
Maximum-Likelihood and Bayesian Parameter Estimation.
Nonparametric Techniques.
Linear Discriminant Functions.
Multilayer Neural Networks.
Stochastic Methods.
Nonmetric Methods.
Algorithm-Independent Machine Learning.
Unsupervised Learning and Clustering.
Appendix.
Index.