Editing Fixed-point arithmetic (section)

==Applications==
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A common use of decimal fixed-point is for storing monetary values, for which the complicated rounding rules of floating-point numbers are often a liability.  For example, the open-source money management application [[GnuCash]], written in C,  switched from floating-point to fixed-point as of version 1.6, for this reason.

Binary fixed-point (binary scaling) was widely used from the late 1960s to the 1980s for real-time computing that was mathematically intensive, such as [[flight simulation]] and in [[nuclear power plant]] control algorithms. It is still used in many [[digital signal processing|DSP]] applications and custom-made microprocessors. Computations involving angles would use [[binary angular measurement]].

Binary fixed point is used in the [[STM32|STM32G4]] series [[CORDIC]] co-processors and in the [[discrete cosine transform]] algorithms used to compress [[JPEG]] images.

Electronic instruments such as [[electricity meter]]s and [[Real-time clock|digital clock]]s often use polynomials to compensate for introduced errors, e.g. from temperature or power supply voltage. The coefficients are produced by [[polynomial regression]]. Binary fixed-point polynomials can utilize more bits of precision than floating-point and do so in fast code using inexpensive CPUs. Accuracy, crucial for instruments, compares well to equivalent-bit floating-point calculations, if the fixed-point polynomials are evaluated using [[Horner's method]] (e.g. {{math|1=''y'' = ((''ax'' + ''b'')''x'' + ''c'')''x'' + ''d''}}) to reduce the number of times that rounding occurs, and the fixed-point multiplications utilize rounding addends.