[Editor's note: For an intro to fixed-point math, see Fixed-Point DSP and Algorithm Implementation. For a comparison of fixed- and floating-point hardware, see Fixed vs. floating point: a surprisingly ...
Floating-point arithmetic provides a practical means of representing real numbers on digital computers by encoding them in a finite number of bits for sign, exponent and significand. The IEEE-754 ...
An unfortunate reality of trying to represent continuous real numbers in a fixed space (e.g. with a limited number of bits) is that this comes with an inevitable loss of both precision and accuracy.
This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American Last month, I wrote about the hype ...
Today’s digital signal processing applications such as radar, echo cancellation, and image processing are demanding more dynamic range and computation accuracy. Floating-point arithmetic units offer ...
Engineers targeting DSP to FPGAs have traditionally used fixed-point arithmetic, mainly because of the high cost associated with implementing floating-point arithmetic. That cost comes in the form of ...
There is a natural preference to use floating-point implementations in custom embedded applications because they offer a much higher dynamic range and as a byproduct bypass the design hassle of ...
In 1985, the Institute of Electrical and Electronics Engineers (IEEE) established IEEE 754, a standard for floating point formats and arithmetic that would become the model for practically all FP ...
Here we provide rational for using Centar’s floating-point IP core for the new Altera Arria 10 and Stratix 10 FPGA platforms. After a short contextual discussion section, a comparison of various FFT ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results