ECE 511

Numeric Modeling of Physics & Biological Systems

Usually offered: Fall

Required course: No

Course Level

Graduate

Units

3

Prerequisite(s)

ECE 381, MATH 254, PHYS 141, PHYS 143, ECE 175, or consult with instructor

Course Texts

  • 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

Course Description

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.

Syllabus Prepared By

Syllabus updated on 7/21/2022

Contact Graduate Advisor: gradadvisor@ece.arizona.edu

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