NDLI: Range estimation of floating-point variables in Simulink models

Content Provider	IEEE Xplore Digital Library
Author	Chapoutot, A. Didier, L. Villers, F.
Copyright Year	2012
Description	Author affiliation: Laboratoire d'informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - France (Didier, L.) \|\| Laboratoire de probabilité et modèles aléatoires (LPMA), Université Pierre et Marie Curie - France (Villers, F.) \|\| Department of Computer Science and System Engineering, ENSTA ParisTech - France (Chapoutot, A.)
Abstract	Fixed-point arithmetic is widely used in embedded applications because it allows to build compact, fast and low-power application-specific integrated circuits designs. Practically, many of them are designed using model-based design tool such as Matlab/Simulink which allow simulations in floating-point representations. From such a high level simulable model, embedded system designers have to size the proper fixed-point representation. Thus, the challenge is to transform floating-point algorithms into numerical equivalent fixed-point programs. As software increases in complexity and both arithmetics do not have the same behaviors, designers need tools to help them in this task. In this article, we present a new statistical method based on Extreme Value Theory to estimate the dynamic range of program variables. We show that this model fits better than Gumbel model to the range estimation in digital signal processing applications both for linear and nonlinear systems. We present several experiments to illustrate the practical use of our approach. We show few simulations are required in order to estimate the bit-width of the bound of the range.
Starting Page	1
Ending Page	8
File Size	975332
Page Count	8
File Format	PDF
ISBN	9781467320894
e-ISBN	9782953998726
e-ISBN	9782953998740
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-23
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	ECSI
Subject Keyword	Statistical method Software packages Computational modeling Dynamic range estimation Estimation Extreme value distribution Numerical models Random variables Mathematical model Manganese Fixed-point arithmetic
Content Type	Text
Resource Type	Article

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