Nicht aus der Schweiz? Besuchen Sie lehmanns.de
Data-Driven Modeling & Scientific Computation - J. Nathan Kutz

Data-Driven Modeling & Scientific Computation

Methods for Complex Systems & Big Data

(Autor)

Buch | Hardcover
658 Seiten
2013
Oxford University Press (Verlag)
978-0-19-966033-9 (ISBN)
CHF 149,95 inkl. MwSt
  • Versand in 15-20 Tagen
  • Versandkostenfrei
  • Auch auf Rechnung
  • Artikel merken
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.
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 used in combination to give critical insight into the fundamental workings of various problems.

Data-Driven Modeling and Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms for data manipulation and analysis. Emphasis is on the implementation of numerical schemes to practical problems in the engineering, biological and physical sciences.

An accessible introductory-to-advanced text, this book fully integrates MATLAB and its versatile and high-level programming functionality, while bringing together computational and data skills for both undergraduate and graduate students in scientific computing.

Professor Kutz is the Robert Bolles and Yasuko Endo Professor of Applied Mathematics at the University of Washington. Prof. Kutz was awarded the B.S. in physics and mathematics from the University of Washington (Seattle, WA) in 1990 and the PhD in Applied Mathematics from Northwestern University (Evanston, IL) in 1994. He joined the Department of Applied Mathematics, University of Washington in 1998 and became Chair in 2007. Professor Kutz is especially interested in a unified approach to applied mathematics that includes modeling, computation and analysis. His area of current interest concerns phenomena in complex systems and data analysis (dimensionality reduction, compressive sensing, machine learning), neuroscience (neuro-sensory systems, networks of neurons), and the optical sciences (laser dynamics and modelocking, solitons, pattern formation in nonlinear optics).

I BASIC COMPUTATIONS AND VISUALIZATION; II DIFFERENTIAL AND PARTIAL DIFFERENTIAL EQUATIONS; III COMPUTATIONAL METHODS FOR DATA ANALYSIS; IV SCIENTIFIC APPLICATIONS

Erscheint lt. Verlag 19.9.2013
Zusatzinfo 200 b/w line drawings, 20 b/w halftones
Verlagsort Oxford
Sprache englisch
Maße 195 x 254 mm
Gewicht 1524 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Theorie / Studium Algorithmen
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Analysis
ISBN-10 0-19-966033-6 / 0199660336
ISBN-13 978-0-19-966033-9 / 9780199660339
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
Datenanalyse für Künstliche Intelligenz

von Jürgen Cleve; Uwe Lämmel

Buch | Softcover (2024)
De Gruyter Oldenbourg (Verlag)
CHF 104,90
Auswertung von Daten mit pandas, NumPy und IPython

von Wes McKinney

Buch | Softcover (2023)
O'Reilly (Verlag)
CHF 62,85