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  2. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    binary real values are represented in a binary format that includes the mantissa, the base (2, 8, or 16), and the exponent; the special values NaN, -INF, +INF , and negative zero are also supported Multiple valid types ( VisibleString, PrintableString, GeneralString, UniversalString, UTF8String )

  3. Scientific notation - Wikipedia

    en.wikipedia.org/wiki/Scientific_notation

    The integer n is called the exponent and the real number m is called the significand or mantissa. [1] The term "mantissa" can be ambiguous where logarithms are involved, because it is also the traditional name of the fractional part of the common logarithm. If the number is negative then a minus sign precedes m, as in ordinary decimal notation.

  4. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    The sum of the exponent bias (127) and the exponent (1) is 128, so this is represented in the single-precision format as 0 10000000 10010010000111111011011 (excluding the hidden bit) = 40490FDB [27] as a hexadecimal number. An example of a layout for 32-bit floating point is and the 64-bit ("double") layout is similar.

  5. Double-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Double-precision_floating...

    Exponent: 11 bits; Significand precision: 53 bits (52 explicitly stored) The sign bit determines the sign of the number (including when this number is zero, which is signed). The exponent field is an 11-bit unsigned integer from 0 to 2047, in biased form: an exponent value of 1023 represents the actual zero. Exponents range from −1022 to ...

  6. Exponential search - Wikipedia

    en.wikipedia.org/wiki/Exponential_search

    If the element at the current index is larger than the search key, the algorithm now knows that the search key, if it is contained in the list at all, is located in the interval formed by the previous search index, 2 j - 1, and the current search index, 2 j. The binary search is then performed with the result of either a failure, if the search ...

  7. Binary logarithm - Wikipedia

    en.wikipedia.org/wiki/Binary_logarithm

    For example, in binary search, the size of the problem to be solved is halved with each iteration, and therefore roughly log 2 n iterations are needed to obtain a solution for a problem of size n. [34] Similarly, a perfectly balanced binary search tree containing n elements has height log 2 (n + 1) − 1. [35]

  8. Subnormal number - Wikipedia

    en.wikipedia.org/wiki/Subnormal_number

    Notice that for a binary radix, the leading binary digit is always 1. In a subnormal number, since the exponent is the least that it can be, zero is the leading significant digit (0.m 1 m 2 m 3...m p−2 m p−1), allowing the representation of numbers closer to zero than the smallest normal number. A floating-point number may be recognized as ...

  9. Exponential tree - Wikipedia

    en.wikipedia.org/wiki/Exponential_tree

    An exponential tree is a type of search tree where the number of children of its nodes decreases doubly-exponentially with increasing depth. Values are stored only in the leaf nodes. Each node contains a splitter, a value less than or equal to all values in the subtree which is used during search.