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Standard form is a way of writing number. ... Extended Precision (80 bits) and with this standard, floating point numbers are represented in the form, s represents the sign of the number. When it comes to the representation, you can see all normal floating-point numbers as a value in the range 1.0 to (almost) 2.0, scaled with a power of two. It will convert a decimal number to its nearest single-precision and double-precision IEEE 754 binary floating-point number, using round-half-to-even rounding (the default IEEE rounding mode). For example, the number 55.66 can be represented as 5.566×10^1 , 0.5566×10^2 , 0.05566×10^3 , … So: 1.0 is simply 1.0 * 2^0, 2.0 is 1.0 * 2^1, and-5.0 is -1.25 * 2^2. If the number is negative, set it to 1. A floating point type variable is a variable that can hold a real number, such as 4320.0, -3.33, or 0.01226. In this situation you know that the number you are storing is rational, so you can avoid all the problems of floating point math by storing it as an integer numerator and denominator. Clearly, using only 32 bits, it's not possible to store every digit in such numbers. Representation of floating point number is not unique. Converting a number to floating point involves the following steps: Set the sign bit - if the number is positive, set the sign bit to 0. Floating point representation Real decimal numbers. About the Decimal to Floating-Point Converter. As we saw with the above example, the non floating point representation of a number can take up an unfeasible number of digits, imagine how many digits you would need to store in binary‽ A binary floating point number may consist of 2, 3 or 4 bytes, however the only ones you need to worry about are the 2 byte (16 bit) variety. The conversion between a floating point number (i.e. a 32 bit area in memory) and the bit representation isn't actually a conversion, but just a reinterpretation of the same data in memory. This is a decimal to binary floating-point converter. IEEE Floating Point Representation. Integers are great for counting whole numbers, but sometimes we need to store very large numbers, or numbers with a fractional component. Divide your number into two sections - the whole number part and the fraction part. This can be easily done with typecasts in C/C++ or with some bitfiddling via java.lang.Float.floatToIntBits in Java. Converting to Floating point.