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Item Details
Title:
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DATA-DRIVEN MODELING & SCIENTIFIC COMPUTATION
METHODS FOR COMPLEX SYSTEMS & BIG DATA |
By: |
J. Nathan Kutz |
Format: |
Hardback |
List price:
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£110.00 |
Our price: |
£96.25 |
Discount: |
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You save:
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£13.75 |
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ISBN 10: |
0199660336 |
ISBN 13: |
9780199660339 |
Availability: |
Usually dispatched within 1-3 weeks.
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Stock: |
Currently 0 available |
Publisher: |
OXFORD UNIVERSITY PRESS |
Pub. date: |
8 August, 2013 |
Pages: |
656 |
Description: |
Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies. |
Synopsis: |
The 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 |
Illustrations: |
200 b/w line drawings, 20 b/w halftones |
Publication: |
UK |
Imprint: |
Oxford University Press |
Returns: |
Returnable |
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