Problems for Midterm Two
- TANT networks. The concept.
- TANT networks. Reduction of minimization of third level to unate covering.
- TANT networks. Reduction of minimization of the entire network to binate covering.
- MMD algorithm for reversible cascade synthesis. Only for those who have related project.
- Using cube calculus for SOP and ESOP minimization, basic CC operations.
Only for those who have related project.
- Iterative circuits. Types of circuits. Systematic design. Inhibition method to minimize logic.
- Ashenhurst Decomposition.
- Curtis Decomposition.
- AND/OR/XOR - bi-decomposition of Boolean Functions.
- The concept of repeated variables and its use in any kind of decomposition, for instance Ashenhurst/Curtis decomposition.
- BDD. Creation of BDD from Shannon Tree. Operations on BDDs.
- ZDD. Creation of BDD from Shannon Tree. Use to represent characteristic functions.
- Characteristic functions to represent boolean relations, graphs and automata.
- MDD - Multiple-valued decision diagrams. Creation of them for complete functions
and functions with don't cares and generalized don't cares.
- Kronecker Functional Decision Diagrams. You have to be able to design a KFDD with Shannon, Positive Davio and Negative Davio nodes, or their subset for a function specified in any form.
- Symmetric functions. Lattices. Structures from multiplexers to realize symmetric functions.
- Realization of symmetric functions with structures called nets.
- The concept of a threshold function. Majority function, its realization and uses.
- Use of repeated variables and lattices to realize threshold functions.
- PLA with decoders and use of Multiple-valued logic to minimize such PLAs.
- Realize Shannon lattice from a set of Kmaps.
- Realize a (Kronecker) Positive Davio lattice from a PPRM expression.
- Walsh Transform and its applications. (not mandatory).
- NPN classification of Boolean functions. (not mandatory).