Pattern Recognition
by William Gibson

Book Description
Cayce Pollard is an expensive, spookily intuitive market-research consultant. In London on a job, she is offered a secret assignment: to investigate some intriguing snippets of video that have been appearing on the Internet. An entire subculture of people is obsessed with these bits of footage, and anybody who can create that kind of brand loyalty would be a gold mine for Cayce's client. But when her borrowed apartment is burgled and her computer hacked, she realizes there's more to this project than she had expected.

Still, Cayce is her father's daughter, and the danger makes her stubborn. Win Pollard, ex-security expert, probably ex-CIA, took a taxi in the direction of the World Trade Center on September 11 one year ago, and is presumed dead. Win taught Cayce a bit about the way agents work. She is still numb at his loss, and, as much for him as for any other reason, she refuses to give up this newly weird job, which will take her to Tokyo and on to Russia. With help and betrayal from equally unlikely quarters, Cayce will follow the trail of the mysterious film to its source, and in the process will learn something about her father's life and death.

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Pattern Recognition, Second Edition
by Sergios Theodoridis, Konstantinos Koutroumbas

Book Description
Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. This volume's unifying treatment covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn". A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.

• Approaches pattern recognition from the designer's point of view.
• New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere.
• Supplemented by computer examples selected from applications of interest.
  

Statistical Pattern Recognition, 2nd Edition
by Andrew R. Webb

Book Description
Statistical pattern recognition is a very active area of study and research, which has seen many advances in recent years. New and emerging applications - such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition - require robust and efficient pattern recognition techniques. Statistical decision making and estimation are regarded as fundamental to the study of pattern recognition.

Statistical Pattern Recognition, Second Edition has been fully updated with new methods, applications and references. It provides a comprehensive introduction to this vibrant area - with material drawn from engineering, statistics, computer science and the social sciences - and covers many application areas, such as database design, artificial neural networks, and decision support systems.

• Provides a self-contained introduction to statistical pattern recognition.
• Each technique described is illustrated by real examples.
• Covers Bayesian methods, neural networks, support vector machines, and unsupervised classification.
• Each section concludes with a description of the applications that have been addressed and with further developments of the theory.
• Includes background material on dissimilarity, parameter estimation, data, linear algebra and probability.
• Features a variety of exercises, from 'open-book' questions to more lengthy projects.

The book is aimed primarily at senior undergraduate and graduate students studying statistical pattern recognition, pattern processing, neural networks, and data mining, in both statistics and engineering departments. It is also an excellent source of reference for technical professionals working in advanced information development environments.