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Course Date: 26 August 2014 to 04 November 2014 (10 weeks)
Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.
J. Nathan Kutz specializes in a unified approach to applied mathematics
including modeling, computation and analysis. His current focus is
phenomena in dimensionality reduction and data-analysis techniques for
complex systems. This includes work in laser dynamics and modelocking in
fiber lasers, neuro-sensory systems and theoretical neuroscience, and
gesture recognition algorithms for portable electronic devices. Kutz has
authored numerous scientific articles on these subjects as well as
segments of books devoted to his area of expertise.
Investigate the flexibility and power of project-oriented computational
analysis. Practice using this technique to resolve complicated
problems in a range of fields including the physical and
engineering sciences, finance and economics, medical, social and
biological sciences. Enhance communication of information by creating
visual representations of scientific data.
This course is a survey of numerical solution techniques for ordinary
and partial differential equations. Emphasis will be on the application
of numerical schemes to practical problems in the engineering and
physical sciences. Apply advanced MATLAB routines and toolboxes to
solve problems. Review and practice graphical techniques for
information presentation and learn to create visual illustrations of
Kutz, N. (2013). Data-driven modeling scientific computation. New York, NY: Oxford University Press.
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