Numerical Simulation and Modeling: EECS 219A, Fall 2017
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Numerical simulation and computational modelling are technologies that pervade science and engineering, from electronics (e.g., analog/RF/mixed-signal circuits, high-speed digital circuits, interconnect, etc.) to optics, nanotechnology, chemistry, biology and mechanics. Moreover, knowing the analytical techniques underlying modelling and simulation is crucial for designing systems. This course provides a detailed introduction to the fundamental principles of these technologies and techniques.
Starting with an introduction to equation-based system modelling, the course covers fundamental concepts and algorithms in numerical simulation, including nonlinear and linear algebraic system solution, numerical algorithms for ODEs and DAEs, frequency-domain solution of linear(ized) systems and algorithms for simulating the effects of noise and parametric variability. Modelling and simulation concepts are developed in the context of system examples so that students are able to apply them immediately to their own research projects. Electronic, mechanical and biochemical systems (including variability-aware and stochastic representations) are used to ground theory and numerics.
The course emphasizes hands-on programming and application to examples as an important means to understand and benefit from the material. Pre-requisites are reviewed in class to make the course as self-contained as possible.
This course is particularly relevant to the BIO, CIR, DMA, INC, MEMS, PHY and SCI areas of EECS, and is a part of Berkeley's Designated Emphasis in Computational Science and Engineering (CSE).
Course format
- The grade for the course will be based on assigned homeworks, a midterm exam, a final examination, and class attendance/participation.
- 4 credits. Class #: 67121.
- MW 1-2:30pm and W 2:30-4pm in 540 Cory Hall.
- Slides/notes will be made available to the students.
- Prof. Jaijeet Roychowdhury.