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<div class="moz-cite-prefix">I think you have answered your own
question. In the literature you will many times see matrices
used in this way to simplify the presentation. The discrete
fourier transform filtering in matrix form is actually<br>
<br>
<img style="vertical-align: middle"
src="cid:part1.03030500.03090005@mercer.edu" alt="${\bf y}=
{\bf \widehat{Z^{-1}}}{\bf \widehat{G}}{\bf \widehat{Z}} {\bf
y}$">.<br>
<br>
Only by dissecting the pieces and actually writing the code can
you sometimes spot the shortcuts.<br>
<br>
<br>
On 12/04/13 21:25, Tapas Misra wrote:<br>
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cite="mid:C40B2F181831EF44A88CD735258278030266A727DE@MERCERMAIL.MercerU.local"
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Dr. Pounds,<br>
<br>
There are three parts of the DFT filtering process:<br>
<br>
1.) The actual Discrete Fourier Transform - in the project
specs handout ( c = Z * y)<br>
<br>
2.) The attentuation process - (c = G * c)<br>
<br>
3.) The Inverse Transform - three methods specified in
handout<br>
<br>
I know parts 1 and 3 must be implemented via matrix methods as
per your instruction. My question is, does part #2 need to be
implemented with Matrix-Vector Multiplication? Since G is a
diagonal matrix, is it acceptable to simply multiply each
component of c by its corresponding attenuation factor without
actually constructing a G matrix?<br>
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<br>
<br>
<pre class="moz-signature" cols="72">--
Andrew J. Pounds, Ph.D. (<a class="moz-txt-link-abbreviated" href="mailto:pounds_aj@mercer.edu">pounds_aj@mercer.edu</a>)
Professor of Chemistry and Computer Science
Mercer University, Macon, GA 31207 (478) 301-5627
<a class="moz-txt-link-freetext" href="http://faculty.mercer.edu/pounds_aj">http://faculty.mercer.edu/pounds_aj</a>
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