The term floating point is derived from the fact that there is no fixed number of digits before and after the decimal point; namely, the decimal point can float. There are also representations in ...

The traditional view is that the floating-point number format is superior to the fixed-point number format when it comes to representing sound digitally. In fact, while it may be counter-intuitive, ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...

Embedded C and C++ programmers are familiar with signed and unsigned integers and floating-point values of various sizes, but a number of numerical formats can be used in embedded applications. Here ...

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.

Most AI chips and hardware accelerators that power machine learning (ML) and deep learning (DL) applications include floating-point units (FPUs). Algorithms used in neural networks today are often ...

This post sponsored by Texas Instruments. The TMS320C672x is the next generation of Texas Instruments' C67x generation of high-performance 32-/64-bit floating-point digital signal processors. The ...

A way to represent very large and very small numbers using the same quantity of numeric positions. Floating point also enables calculating a wide range of numbers very quickly. Although floating point ...