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Hexadecimal (also known as base-16 or simply hex) is a positional numeral system that represents numbers using a radix (base) of sixteen. Unlike the decimal system representing numbers using ten symbols, hexadecimal uses sixteen distinct symbols, most often the symbols "0"–"9" to represent values 0 to 9 and "A"–"F" to represent values from ten to fifteen.
Mapping the nonzero digits to the alphabet and zero to the space is occasionally used to provide checksums for alphabetic data such as personal names, [54] to provide a concise encoding of alphabetic strings, [55] or as the basis for a form of gematria. [56] Compact notation for ternary. 28: Months timekeeping. 30: Trigesimal
Well-known positional number systems for the complex numbers include the following (being the imaginary unit): , , e.g. , [1] and , , [2] the quater-imaginary base, proposed by Donald Knuth in 1955.
Base36 is a binary-to-text encoding scheme that represents binary data in an ASCII string format by translating it into a radix-36 representation. The choice of 36 is convenient in that the digits can be represented using the Arabic numerals 0–9 and the Latin letters A–Z (the ISO basic Latin alphabet). Each base36 digit needs less than 6 ...
If X is a Banach space with a Schauder basis {e n} n ≥ 1 such that the biorthogonal functionals are a basis of the dual, that is to say, a Banach space with a shrinking basis, then the space K(X) admits a basis formed by the rank one operators e* j ⊗ e k : v → e* j (v) e k, with the same ordering as before. [17]
Also, because it encodes five 8-bit bytes (40 bits) to eight 5-bit base32 characters rather than three 8-bit bytes (24 bits) to four 6-bit base64 characters, padding to an 8-character boundary is a greater burden on short messages (which may be a reason to elide padding, which is an option in RFC 4648).
The classical normal basis theorem states that there is an element such that {():} forms a basis of K, considered as a vector space over F. That is, any element α ∈ K {\displaystyle \alpha \in K} can be written uniquely as α = ∑ g ∈ G a g g ( β ) {\textstyle \alpha =\sum _{g\in G}a_{g}\,g(\beta )} for some elements a g ∈ F ...
Radial basis function (RBF) interpolation is an advanced method in approximation theory for constructing high-order accurate interpolants of unstructured data, possibly in high-dimensional spaces. The interpolant takes the form of a weighted sum of radial basis functions .