?? matlab file least-squares polynomial approximations.mht
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Subject: Matlab File: Least-squares polynomial approximations
Date: Thu, 12 Apr 2007 11:50:14 +0800
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<H3>Matlab =
File(s)</H3></TD></TR></TBODY></TABLE>
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<TD><B>Title:</B></TD>
<TD>Least-squares polynomial =
approximations=20
</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>Author:</B></TD>
<TD>Alain Kapitho</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>E-Mail:</B></TD>
<TD><A=20
=
href=3D"mailto:kaps-AT-tuks.co.za">kaps-AT-tuks.co.za</A>=20
</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>Institution:</B></TD>
<TD><A =
href=3D"http://www.up.ac.za/">University of=20
Pretoria</A> </TD></TR>
<TR bgColor=3D#ffffff>
<TD vAlign=3Dtop><B>Description: =
</B></TD>
<TD>Function least_squares(x, y, m) fits =
a=20
least-squares polynomial of degree m =
through=20
data points given in x-y coordinates. =
the output=20
to the function is a vector c =3D [c0, =
c1, ...,=20
cm] whose components are the =
coefficients of the=20
polynomial. The function can also be =
used in the=20
following sense: least_squares(x, =
log(x), 1) -=20
this will linearize data that obey an=20
exponential curve y =3D b*exp(a*x) and =
the output=20
c =3D [c0, c1] =3D [ln b, a]. Also, =
least_squares(x,=20
1./y, 1) linearizes data that follow a =
model y =3D=20
1/(ax + b). In other words, various =
combinations=20
can be tested to linearize data (m=3D1) =
and from=20
the graph display, we can see which =
combination=20
linarizes data best </TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>Keywords:</B></TD>
<TD>Least-squares, curve fitting =
</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>File Name: </B></TD>
<TD>least_squares.m</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>File Size: </B></TD>
<TD>2 KB </TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>File Version: </B></TD>
<TD>1.0</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>Matlab Version: </B></TD>
<TD>7.0 (R14)</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>Date: </B></TD>
<TD>2006-01-11</TD></TR>
<TR bgColor=3D#ffffff>
<TD><B>Downloads: </B></TD>
<TD>917</TD></TR>
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