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How would you describe the flickering of a flame? The twinkling of stars? A bowling ball hitting pins? The texture of an oil painting? Melting ice? Traffic on Route 93 during rush hour? The sound of a cello? The flight of a paper airplane? Breaking glass? The spread of a rumor? A bowl of jello? Digital systems are routinely used to model natural systems for purposes ranging from transmitting realities, to experimenting with possibilities, to realizing fantasies.
This course will survey the useful levels of description for such mathematical modeling, including analytical techniques, numerical methods, and model estimation. The focus will be on understanding how the methods interrelate, and on how they can be implemented efficiently.
| Instructor | : Prof. Neil Gershenfeld |
| T.A. | : Jim McBride |
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| Schedule | |
|---|---|
| 2/10 | Introduction, graphics, and math environments |
| 2/18 | Ordinary differential and difference equations |
| 2/24 | Finite differences: ordinary differential equations |
| 3/3 | Finite differences: partial differential equations |
| 3/10 | Cellular automata and lattice gases |
| 3/17 | Random systems |
| 3/31 | Function fitting |
| 4/7 | Transforms and representations |
| 4/14 | Optimization and search |
| 4/28 | Graphical probabilistic networks |
| 5/5 | Symmetry |
| 5/12 | Control |
| 5/19 | Projects |
Lectures: Monday 1:00-4:00 in room E15-054.
Recitations: Friday 1:00-2:00 in room E15-054.
Units: 3-0-9