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	<title>Comments for Cognitive Radio Project</title>
	<atom:link href="http://cr.jamesyxu.com/?feed=comments-rss2" rel="self" type="application/rss+xml" />
	<link>http://cr.jamesyxu.com</link>
	<description>A 4th Year Project by James Xu (Dr. Fakhrul Alam as Supervisor), Massey University, Auckland, New Zealand</description>
	<lastBuildDate>Thu, 05 Nov 2009 06:11:27 -0800</lastBuildDate>
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		<title>Comment on Preliminary wideband channel sensor by mudasir</title>
		<link>http://cr.jamesyxu.com/?p=139&#038;cpage=1#comment-103</link>
		<dc:creator>mudasir</dc:creator>
		<pubDate>Thu, 05 Nov 2009 06:11:27 +0000</pubDate>
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		<description>Hello

where is the report</description>
		<content:encoded><![CDATA[<p>Hello</p>
<p>where is the report</p>
]]></content:encoded>
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		<title>Comment on Cyclostationary feature extraction through SCF by mudasir</title>
		<link>http://cr.jamesyxu.com/?p=247&#038;cpage=1#comment-102</link>
		<dc:creator>mudasir</dc:creator>
		<pubDate>Thu, 05 Nov 2009 06:00:52 +0000</pubDate>
		<guid isPermaLink="false">http://cr.jamesyxu.com/?p=247#comment-102</guid>
		<description>Hello

I have been going through cyclostationary and found that u have are working on cyclostationary. I was working with cyclostationary toolbox to find out cyclostationary features of BPSK and QPSK signals. I will send u my code  also available on pudn cyclostationar tool box SCD for cyclic autocorrelation. it gives good result for BPSK but for QPSK and others (e.g 8psk) it gives the same result as BPSK. while there is a difference between features of BPSK and QPSK as in QPSK alpha=2xfc doesn’t have a peak. but for this algo I find the peak at alpha=2xfc for QPSK as well. How do I classify my signals. Why doesn’t this I and Q components cancels their effects in my case?

regards
Madd</description>
		<content:encoded><![CDATA[<p>Hello</p>
<p>I have been going through cyclostationary and found that u have are working on cyclostationary. I was working with cyclostationary toolbox to find out cyclostationary features of BPSK and QPSK signals. I will send u my code  also available on pudn cyclostationar tool box SCD for cyclic autocorrelation. it gives good result for BPSK but for QPSK and others (e.g 8psk) it gives the same result as BPSK. while there is a difference between features of BPSK and QPSK as in QPSK alpha=2xfc doesn’t have a peak. but for this algo I find the peak at alpha=2xfc for QPSK as well. How do I classify my signals. Why doesn’t this I and Q components cancels their effects in my case?</p>
<p>regards<br />
Madd</p>
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		<title>Comment on Cyclostationary feature extraction through SCF by yuexin</title>
		<link>http://cr.jamesyxu.com/?p=247&#038;cpage=1#comment-101</link>
		<dc:creator>yuexin</dc:creator>
		<pubDate>Sat, 10 Oct 2009 07:49:24 +0000</pubDate>
		<guid isPermaLink="false">http://cr.jamesyxu.com/?p=247#comment-101</guid>
		<description>Thank you very much</description>
		<content:encoded><![CDATA[<p>Thank you very much</p>
]]></content:encoded>
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	<item>
		<title>Comment on Cyclostationary feature extraction through SCF by James</title>
		<link>http://cr.jamesyxu.com/?p=247&#038;cpage=1#comment-100</link>
		<dc:creator>James</dc:creator>
		<pubDate>Sat, 10 Oct 2009 07:27:05 +0000</pubDate>
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		<description>as you may have noticed, the cyclostationary feature extraction is not my main area of focus, as my time is short (1 year project). 

As a result, the code is proof of concept only, and is a direct implementation of the methods mentioned in the papers (linked in the post). We may open our codebase (SVN) at the end of the year, in about 2 weeks, so you may want to check back on the blog and see if we have any updates</description>
		<content:encoded><![CDATA[<p>as you may have noticed, the cyclostationary feature extraction is not my main area of focus, as my time is short (1 year project). </p>
<p>As a result, the code is proof of concept only, and is a direct implementation of the methods mentioned in the papers (linked in the post). We may open our codebase (SVN) at the end of the year, in about 2 weeks, so you may want to check back on the blog and see if we have any updates</p>
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		<title>Comment on Cyclostationary feature extraction through SCF by yuexin</title>
		<link>http://cr.jamesyxu.com/?p=247&#038;cpage=1#comment-99</link>
		<dc:creator>yuexin</dc:creator>
		<pubDate>Sat, 10 Oct 2009 07:21:12 +0000</pubDate>
		<guid isPermaLink="false">http://cr.jamesyxu.com/?p=247#comment-99</guid>
		<description>hello 
i&#039;m working on spectrum sensing techniques in cognitive 
radio...it is an emerging topic and we don&#039;t find any codes 
or any help for it. And here , i find this projec can help me ,
so it&#039;s very kind of you to send me some matlab code...
it would be the greatest help for me in doing my project... 


thank u in advance</description>
		<content:encoded><![CDATA[<p>hello<br />
i&#8217;m working on spectrum sensing techniques in cognitive<br />
radio&#8230;it is an emerging topic and we don&#8217;t find any codes<br />
or any help for it. And here , i find this projec can help me ,<br />
so it&#8217;s very kind of you to send me some matlab code&#8230;<br />
it would be the greatest help for me in doing my project&#8230; </p>
<p>thank u in advance</p>
]]></content:encoded>
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		<title>Comment on Very good articles &#8211; Part 1 by Ebrahim</title>
		<link>http://cr.jamesyxu.com/?p=125&#038;cpage=1#comment-98</link>
		<dc:creator>Ebrahim</dc:creator>
		<pubDate>Sun, 20 Sep 2009 19:26:48 +0000</pubDate>
		<guid isPermaLink="false">http://cr.jamesyxu.com/?p=125#comment-98</guid>
		<description>Thanks for sharing, this is so helpful. Waiting for the second part.</description>
		<content:encoded><![CDATA[<p>Thanks for sharing, this is so helpful. Waiting for the second part.</p>
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