A real number held as a pair of integers, one representing the mantissa and the other representing the exponent. The base is normally 10, 16 or 256 depending on the computing system
A microprocessor that performs floating-point arithmetic. In older models of computer the FPU was not integrated into the central processing unit, but rather as a coprocessor if included at all
Often referred to in mathematical terms as a "rational" or real number, this is just a number that can have a fractional part See also "Double-Precision" and "Single-Precision "
A real number that is represented by a pair of distinct numerals The real number is the product of the fractional part, one of the numerals, and a value obtained by raising the implicit floating-point base to a power indicated by the second numeral
an approximate representation of a real number value in scientific notation, consisting of a fractional part (mantissa) and an exponent E g 0 196E31 represents the number 0 196 10^31
A technique for representing numbers without using a fixed-position point in order to improve the calculating capability of the CPU for arithmetic with real numbers
Scientific notation; a form of representation of numbers in which the number is represented in two parts, the argument or fixed-point part, and the exponent The exponent is that power of the radix by which the argument must be multiplied to give the true value of the number The use of floating-point representation and arithmetic in a computer facilitates storage and manipulation of numbers in a wider range of magnitudes than is normally practicable and with a consistent relative degree of precision
A representation for rational numbers (and an approximation for real numbers) that uses 32 bits of storage In Java, implemented by the primitive type float Contrast double precision floating point
Calculations that use an exponent with numbers to indicate the location of the decimal "floating" point is known as Floating Point Arithmetic These numbers have two parts: a mantissa and an exponent The mantissa designates the digits in the number and the exponent designates the position of the decimal point
The representation of numbers in terms of mantissa and base raised to some power so that the decimal point floats during calculations; scientific notation
A method of representing numbers in which the decimal (binary) point is permitted to "float" to different locations within the number Some of the bits devoted to storing the number are devoted to keeping track of the point
This is a particular way of representing numbers on computers similar to the scientific notation for writing numbers (e g 0 31415 x 101 also written as 0 31415E1 by computers where `E1' means `x 101') It is almost universally used to represent numbers that are not integers (0,1,2 ) Operations such as addition, multiplication and division using these number are usually the most time consuming parts of scientific computations and the number of such operations that can be performed each second is used as a (crude) measure of computer performance See FLOPS
A number whose bit structure is composed of a mantissa and exponent, whose ASCII representation contains an explicit decimal point and may include a power-of-ten exponent
A binary data type type used to hold a numerical value while allowing the number of decimal places to float or move around Much like the way the decimal point moves around on a calculator automatically as more or less precision is necessary to represent a number There are many standard storage formats for floating point values Compare to integer
A decimal point with a location that is not fixed so it can accommodate numbers of varying lengths before or after the decimal point Often used in computer operations
The term floating point is derived from the fact that there is no fixed number of digits before or after the decimal point; that is, the decimal point can float A floating point number is a real number, a number that can contain a fractional part
In computer operations, a positional notation in which corresponding places in different quantities are not necessarily occupied by coefficient of the same power of the base Compare fixed point