Numeric Modeling of Physics & Biological Systems
- Numeric Modeling of Physics & Biological Systems, W. Fink (class notes)
- Numerical Recipes in C: The Art of Scientific Computing, W.H. Press, B.P. Flannery, S.A. Teukolsky, et al., Cambridge University Press, Cambridge, NY
- MATLAB for Engineers, H. Moore, 3rd Edition, Pearson
- Theoretical Physics on the Personal Computer, E.W. Schmid, G. Spitz, W. Loesch, 2nd Ed., Springer, ISBN-10: 3540522433, ISBN-13: 978-3540522430
- Neural Networks: An Introduction, B. Mueller, J. Reinhardt, Berlin: Springer
- Introduction to the Theory of Neural Computation (Lecture Notes Vol. 1), J. Hertz, A. Krogh, R.G. Palmer, Reading, MA: Addison-Wesley
- Genetic Algorithms in Search, Optimization and Machine Learning, D.E. Goldberg, Addison-Wesley, 1989
This course combines themes from mechanics, electromagnetics, thermal physics, and neural networks with an introduction to numerical methods as well as the use of MATLAB. Students will become familiar with the underlying theory for a variety of systems in physics and biology (e.g., harmonic, anharmonic and coupled oscillators; electric fields of electric lenses; geo-thermal power station; and artificial neural networks), derive the necessary mathematical equations describing these systems, learn the necessary numerical methods to solve the underlying equations, and implement the system equations and numerical methods in MATLAB to simulate these systems. As a result, students will be prepared to formulate problems or model systems in physics, biology, and related disciplines, and to solve them numerically or in simulation.
- Approximately 10 homework sets, including Matlab exercises, during semester.
- Two midterm and one final written examinations.