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authorMichaŽl Baudin <michael.baudin@scilab.org>2009-12-17 11:39:35 +0100
committerMichaŽl Baudin <michael.baudin@scilab.org>2009-12-17 11:39:35 +0100
commit66357908aa69c5c1323d58a0b8e78d81fbb2ab26 (patch)
tree91ca726b251375c773b39c9a8f51303dfe2bb667 /scilab_doc
parent486fcb6567230091d3576e7dbb6cb720cca62d32 (diff)
parent3886ff24a1f980b439c78ce80acea24ed9ba2c9b (diff)
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@@ -92,7 +92,7 @@
92\begin{document} 92\begin{document}
93\author{Michael Baudin} 93\author{Michael Baudin}
94\date{February 2009} 94\date{February 2009}
95\title{Scilab is not naÔve} 95\title{Scilab is not naive}
96\maketitle 96\maketitle
97\begin{abstract} 97\begin{abstract}
98Most of the time, the mathematical formula is 98Most of the time, the mathematical formula is
@@ -103,13 +103,14 @@ the computer does not process mathematical real values,
103but performs computations with their floating 103but performs computations with their floating
104point representation. 104point representation.
105The goal of this article is to show that, in many 105The goal of this article is to show that, in many
106situations, Scilab is not naÔve and use algorithms 106situations, Scilab is not naive and use algorithms
107which have been specifically tailored for floating point 107which have been specifically tailored for floating point
108computers. We analyse in this article the 108computers. We analyse in this article the
109particular case of the quadratic equation, the 109particular case of the quadratic equation, the
110complex division and the numerical derivatives, 110complex division and the numerical derivatives.
111and show that one these examples, the naÔve algorithm 111In each example, we show that the naive algorithm
112is not sufficiently accurate. 112is not sufficiently accurate, while Scilab's implementation
113is much more accurate.
113\end{abstract} 114\end{abstract}
114 115
115\tableofcontents 116\tableofcontents