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MARC 21

Data-driven modeling & scientific computation: methods for complex systems & big data
Tag	Description
020	$a9780199660346
080	$a517.1
082	$a501.5195 (DDC 23)
099	$a517.1 KUT
100	$aKutz, Jose Nathan
245	$aData-driven modeling & scientific computation$bmethods for complex systems & big data$hM$cJ. Nathan Kutz,
260	$aOxford, United Kingdom$bOxford University Press$c2013
300	$axvii, 638 pages$billustrations (some color)$c26 cm.
520	$aThe burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered in the sciences provide an incentive to develop mathematical techniques and computational algorithms that help synthesize, interpret and give meaning to the data in the context of its scientific setting. A specific aim of this book is to integrate standard scientific computing methods with data analysis. By doing so, it brings together, in a self-consistent fashion, the key ideas from: * statistics, * time-frequency analysis, and * low-dimensional reductions The blend of these ideas provides meaningful insight into the data sets one is faced with in every scientific subject today, including those generated from complex dynamical systems. This is a particularly exciting field and much of the final part of the book is driven by intuitive examples from it, showing how the three areas can be Review: The book allows methods for dealing with large data to be explained in a logical process suitable for both undergraduate and post-graduate students ... With sport performance analysis evolving into deal with big data, the book forms a key bridge between mathematics and sport science John Francis, University of Worcester