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.
| ISBN: | 9780387954714 |
| Publication date: | 15th January 2003 |
| Author: | David D Denison |
| Publisher: | Springer an imprint of Springer New York |
| Format: | Paperback |
| Pagination: | 474 pages |
| Series: | Lecture Notes in Statistics |
| Genres: |
Probability and statistics |
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.
Nonlinear Estimation and Classification features in the following genres: Probability and statistics
Nonlinear Estimation and Classification is available in Paperback
Nonlinear Estimation and Classification was written by David D Denison and published by Springer an imprint of Springer New York
Nonlinear Estimation and Classification has 474 pages
Yes it is part of Lecture Notes in Statistics series