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Lecture Notes in Statistics

Nonlinear Estimation and Classification

Editors: Denison, D.D., Hansen, M.H., Holmes, C.C., Mallick, B., Yu, B. (Eds.)

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About this book

Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future.

Table of contents (32 chapters)

Table of contents (32 chapters)

Buy this book

eBook $79.99
price for USA in USD
  • ISBN 978-0-387-21579-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $99.99
price for USA in USD
  • ISBN 978-0-387-95471-4
  • Free shipping for individuals worldwide. COVID-19 shipping restrictions apply.
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Nonlinear Estimation and Classification
Editors
  • David D. Denison
  • Mark H. Hansen
  • Christopher C. Holmes
  • Bani Mallick
  • Bin Yu
Series Title
Lecture Notes in Statistics
Series Volume
171
Copyright
2003
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-0-387-21579-2
DOI
10.1007/978-0-387-21579-2
Softcover ISBN
978-0-387-95471-4
Series ISSN
0930-0325
Edition Number
1
Number of Pages
VII, 477
Topics

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