Assume we use a binary floating-point arithmetic and that RN is the round-to-nearest function. Also assume that c is a constant or a real function of one or more variables, and that we have at our disposal a correctly rounded implementation of c, say ĉ = RN(c). For evaluating x • c (resp. x/c or c/x), the natural way is to replace it by RN(x • ĉ) (resp. RN(x/ĉ) or RN(ĉ/x)), that is, to call function ĉ and to perform a floating-point multiplication or division. This can be generalized to the approximation of n/d by RN(n̂ / d̂ ) and the approximation of n • d by RN(n̂ • d̂ ), where n̂ = RN(n) and d̂ = RN(d), and n and d are functions for which we have at our disposal a correctly rounded implementation. We discuss tight error bounds in ulps of such approximations. From our results, one immediately obtains tight error bounds for calculations such as x * pi, ln(2)/x, x/(y + z), (x + y) * z, x/sqrt(y), sqrt(x)/y, (x + y)(z + t), (x + y)/(z + t), (x + y)/(zt), etc. in floating-point arithmetic.

The computation of Fast Fourier Transforms (FFTs) in floating-point arithmetic is inexact due to roundings, and for some applications it can prove very useful to know a tight bound on the final error. Although it can be almost attained by specifically built input values, the best known error bound for the Cooley-Tukey FFT seems to be much larger than most actually obtained errors. Also, interval arithmetic can be used to compute a bound on the error committed with a given set of input values, but it is in general considered hampered with large overestimation. We report results of intensive computations to test the two approaches, in order to estimate the numerical performance of state-of-the-art bounds. Surprisingly enough, we observe that while interval arithmetic-based bounds are overestimated, they remain, in our computations, tighter than general known bounds.

Experimental link quality assessment of recent Wi-Fi networks remains a challenge due to the rapid development of the Wi-Fi technology, the lack of availability of public datasets, and the difficulty to build such datasets. This paper addresses all three issues by first providing a publicly-available dataset using a custom-made Wi-Fi 5 experimental testbed. We then present an open-source framework for estimating the Frame Delivery Ratio (FDR) of a Wi-Fi link using the experimental data. The proposed solution relies on a small number of input features to build an estimation model of high accuracy, with an R2 coefficient of 0.89 and a mean absolute error of 0.06.

We consider the computation of the Euclidean (or L2) norm of an n -dimensional vector in floating-point arithmetic. We review the classical solutions used to avoid spurious overflow or underflow and/or to obtain very accurate results. We modify a recently published algorithm (that uses double-word arithmetic) to allow for a very accurate solution, free of spurious overflows and underflows. To that purpose, we use a double-word square-root algorithm of which we provide a tight error analysis. The returned L2 norm will be within very slightly more than 0.5 ulp from the exact result, which means that we will almost always provide correct rounding.

We are interested in obtaining error bounds for the classical Cooley-Tukey fast Fourier transform algorithm in floating-point arithmetic, for the 2-norm as well as for the infinity norm. For that purpose, we also give some results on the relative error of the complex multiplication by a root of unity, and on the largest value that can take the real or imaginary part of one term of the fast Fourier transform of a vector x , assuming that all terms of x have real and imaginary parts less than some value b .

Triple-word arithmetic consists in representing high-precision numbers as the unevaluated sum of three floating-point numbers (with “nonoverlapping” constraints that are explicited in the paper). We introduce and analyze various algorithms for manipulating triple-word numbers: rounding a triple-word number to a floating-point number, adding, multiplying, dividing, and computing square-roots of triple-word numbers, etc. We compare our algorithms, implemented in the Campary library, with other solutions of comparable accuracy. It turns out that our new algorithms are significantly faster than what one would obtain by just using the usual floating-point expansion algorithms in the special case of expansions of length 3.