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An n-bit LUT can encode any n-input Boolean function by storing the truth table of the function in the LUT. This is an efficient way of encoding Boolean logic functions, and LUTs with 4-6 bits of input are in fact the key component of modern field-programmable gate arrays (FPGAs) which provide reconfigurable hardware logic capabilities.
For example, (x 1 ∨ ¬x 2) ∧ (¬x 1 ∨ x 2 ∨ x 3) ∧ ¬x 1 is not a Horn formula, but can be renamed to the Horn formula (x 1 ∨ ¬x 2) ∧ (¬x 1 ∨ x 2 ∨ ¬y 3) ∧ ¬x 1 by introducing y 3 as negation of x 3. In contrast, no renaming of (x 1 ∨ ¬x 2 ∨ ¬x 3) ∧ (¬x 1 ∨ x 2 ∨ x 3) ∧ ¬x 1 leads to a Horn formula ...
A closed formula, also ground formula or sentence, is a formula in which there are no free occurrences of any variable. If A is a formula of a first-order language in which the variables v 1, …, v n have free occurrences, then A preceded by ∀v 1 ⋯ ∀v n is a universal closure of A.
A sigmoid function is any mathematical function whose graph has a characteristic S-shaped or sigmoid curve. A common example of a sigmoid function is the logistic function, which is defined by the formula: [1] = + = + = ().
The floor function appears in several formulas characterizing prime numbers. For example, since ⌊ ⌋ ⌊ ⌋ is equal to 1 if m divides n, and to 0 otherwise, it follows that a positive integer n is a prime if and only if [30]
The quadratic formula =. is a closed form of the solutions to the general quadratic equation + + =. More generally, in the context of polynomial equations, a closed form of a solution is a solution in radicals; that is, a closed-form expression for which the allowed functions are only n th-roots and field operations (+,,, /).
It is assumed that the value of a function f defined on [,] is known at + equally spaced points: < < <.There are two classes of Newton–Cotes quadrature: they are called "closed" when = and =, i.e. they use the function values at the interval endpoints, and "open" when > and <, i.e. they do not use the function values at the endpoints.
It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision. [2]