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A representation of a value using binary scaling is more precise than a floating-point representation occupying the same number of bits, but typically represents values of a more limited range, therefore more easily leading to [[arithmetic overflow]] during computation. Implementation of operations using integer arithmetic instructions is often (but not always) faster than the corresponding floating-point instructions.
A position for the 'binary point' is chosen for each variable to be represented, and binary shifts associated with arithmetic operations are adjusted accordingly. The binary scaling corresponds in [[Q (number format)]] to the first digit, i.e. Q1.15 is a 16 bit integer scaled with one bit as integer and fifteen as fractional. A Bscal 1 or Q1.15 number would represent approximately
To give an example, a common way to use [[arbitrary-precision arithmetic|integer arithmetic]] to simulate floating point, using 32-bit numbers, is to multiply the coefficients by 65536.
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