1. REPRESENTATIONS OF DISCRETE DATA.

1. Introduction, grading, class information.
2. Representation vs. strategy vs. optimisation problem: area, speed, power, testability.
3. Role of representations.
4. Functions, relations, sets of functions, sets of relations. State machines. Characteristic functions.
5. Tables.
6. Arrays of cubes.
7. Netlists and graphs of Cube Arrays.
8. Partitions and Labeled Rough Partitions.
9. Binary Decision Trees.
10. Binary Decision Diagrams.
11. Kronecker and other Decision Diagrams.
12. Multi-Valued Decision Diagrams.