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A Boolean function can be represented as a rooted, directed, acyclic graph, which consists of several (decision) nodes and two terminal nodes. The two terminal nodes are labeled 0 (FALSE) and 1 (TRUE). Each (decision) node is labeled by a Boolean variable and has two child nodes called low child and high child.
A comparison of 5 clipping libraries at rogue-modron.blogspot.com; A commercial library for 3D Boolean operations: sgCore C++/C# library. The comp.graphics.algorithms FAQ, solutions to mathematical problems with 2D and 3D Polygons. Matthias Kramm's gfxpoly, a free C library for 2D polygons (BSD license).
In Boolean algebra, Petrick's method [1] (also known as Petrick function [2] or branch-and-bound method) is a technique described by Stanley R. Petrick (1931–2006) [3] [4] in 1956 [5] [6] for determining all minimum sum-of-products solutions from a prime implicant chart. [7]
A Boolean value is either true or false. A Boolean expression may be composed of a combination of the Boolean constants True/False or Yes/No, Boolean-typed variables, Boolean-valued operators, and Boolean-valued functions. [1] Boolean expressions correspond to propositional formulas in logic and are a special case of Boolean circuits. [2]
For example, (a > 0 and not flag) and (a > 0 && !flag) specify the same behavior. As another example, the bitand keyword may be used to replace not only the bitwise-and operator but also the address-of operator, and it can be used to specify reference types (e.g., int bitand ref = n ).
In this example, because someCondition is true, this program prints "1" to the screen. Use the ?: operator instead of an if-then-else statement if it makes your code more readable; for example, when the expressions are compact and without side-effects (such as assignments).
A truth table is a mathematical table used in logic—specifically in connection with Boolean algebra, Boolean functions, and propositional calculus—which sets out the functional values of logical expressions on each of their functional arguments, that is, for each combination of values taken by their logical variables. [1]
By formulating MAX-2-SAT as a problem of finding a cut (that is, a partition of the vertices into two subsets) maximizing the number of edges that have one endpoint in the first subset and one endpoint in the second, in a graph related to the implication graph, and applying semidefinite programming methods to this cut problem, it is possible to ...