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	<title>Comments for Reflections</title>
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	<link>http://shalin.wordpress.com</link>
	<description>Shalin&#039;s homepage and blog</description>
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		<title>Comment on What is systems biology? by biointelligence</title>
		<link>http://shalin.wordpress.com/2006/04/14/what-is-systems-biology/#comment-94</link>
		<dc:creator>biointelligence</dc:creator>
		<pubDate>Thu, 22 Oct 2009 07:40:53 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/2006/04/14/what-is-systems-biology/#comment-94</guid>
		<description>Nice info !!! 
More on Systems Biology can be found here:
http://biointelligence.wordpress.com/tag/systems-biology/</description>
		<content:encoded><![CDATA[<p>Nice info !!!<br />
More on Systems Biology can be found here:<br />
<a href="http://biointelligence.wordpress.com/tag/systems-biology/" rel="nofollow">http://biointelligence.wordpress.com/tag/systems-biology/</a></p>
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		<title>Comment on Impressive 3D optical illusion by Dan Franzen</title>
		<link>http://shalin.wordpress.com/2009/08/18/impressive-3d-optical-illusion/#comment-91</link>
		<dc:creator>Dan Franzen</dc:creator>
		<pubDate>Thu, 15 Oct 2009 18:11:15 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=202#comment-91</guid>
		<description>I have to say that I&#039;m mystified by some of those so-called optical illusions on the Scientific American page. I can see the issue with the Pisa tower, but none of the other ones seem to be illusory at all. For example, the Petronus Towers. The text claims that to us the towers appear to be converging as our eye travels from bottom to top - with the idea being that objects in the distance converge - but to my eye this is completely untrue: the distance between the towers at the top looks exactly the same as that at the bottom. There is no illusion.</description>
		<content:encoded><![CDATA[<p>I have to say that I&#8217;m mystified by some of those so-called optical illusions on the Scientific American page. I can see the issue with the Pisa tower, but none of the other ones seem to be illusory at all. For example, the Petronus Towers. The text claims that to us the towers appear to be converging as our eye travels from bottom to top &#8211; with the idea being that objects in the distance converge &#8211; but to my eye this is completely untrue: the distance between the towers at the top looks exactly the same as that at the bottom. There is no illusion.</p>
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		<title>Comment on Before the start of Frontiers in Optics &#8211; travel and lab visits by S. Barwick</title>
		<link>http://shalin.wordpress.com/2009/10/11/before-the-start-of-frontiers-in-optics-travel-and-lab-visits/#comment-89</link>
		<dc:creator>S. Barwick</dc:creator>
		<pubDate>Wed, 14 Oct 2009 18:51:11 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=379#comment-89</guid>
		<description>Thanks for the great reports!  A site I plan on taking in on my next trip to San Francisco is the Marine Mammal Center, which is a hospital for rehabilitating injured marine mammals. If you are interested in sea lions and such, it might be worth a visit.</description>
		<content:encoded><![CDATA[<p>Thanks for the great reports!  A site I plan on taking in on my next trip to San Francisco is the Marine Mammal Center, which is a hospital for rehabilitating injured marine mammals. If you are interested in sea lions and such, it might be worth a visit.</p>
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		<title>Comment on Impressive 3D optical illusion by Joseph Chan</title>
		<link>http://shalin.wordpress.com/2009/08/18/impressive-3d-optical-illusion/#comment-86</link>
		<dc:creator>Joseph Chan</dc:creator>
		<pubDate>Mon, 12 Oct 2009 11:31:42 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=202#comment-86</guid>
		<description>Dear Shalin:
Really love this paper dragon illusion. Do you have any idea where I can find more of the likes? I believe I&#039;ve seen a few that do similar tricks but for buildings and scenery in an art show earlier this year but have no idea where to start looking.
Or would you know of any tips on the next on how to create illusions like these ones yourself?
Much appreciated!</description>
		<content:encoded><![CDATA[<p>Dear Shalin:<br />
Really love this paper dragon illusion. Do you have any idea where I can find more of the likes? I believe I&#8217;ve seen a few that do similar tricks but for buildings and scenery in an art show earlier this year but have no idea where to start looking.<br />
Or would you know of any tips on the next on how to create illusions like these ones yourself?<br />
Much appreciated!</p>
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		<title>Comment on Phase-space optics 1: Introduction by Shalin Mehta</title>
		<link>http://shalin.wordpress.com/2009/09/07/thoughts-on-phase-space-optics-1/#comment-81</link>
		<dc:creator>Shalin Mehta</dc:creator>
		<pubDate>Thu, 08 Oct 2009 04:20:58 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=237#comment-81</guid>
		<description>Thanks for thought-provoking comments. Without your comments, this issue wouldn&#039;t be so clear. I find Leon Cohen&#039;s book and papers very readable and insightful for such aspects. </description>
		<content:encoded><![CDATA[<p>Thanks for thought-provoking comments. Without your comments, this issue wouldn&#8217;t be so clear. I find Leon Cohen&#8217;s book and papers very readable and insightful for such aspects.</p>
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		<title>Comment on Phase-space optics 1: Introduction by S. Barwick</title>
		<link>http://shalin.wordpress.com/2009/09/07/thoughts-on-phase-space-optics-1/#comment-80</link>
		<dc:creator>S. Barwick</dc:creator>
		<pubDate>Wed, 07 Oct 2009 18:22:48 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=237#comment-80</guid>
		<description>I see your point.  The standard interpretation of the uncertainty principle seems to be that the inability to measure inverse quantities simultaneously is a property of the system itself, not the measurement device, which is not true for deterministic signals.  By contrast, my analogy (not an exact one) pertains to how the measurement is mathematically made with a particular phase-space distribution.  The connection is that both ultimately stem from the time-bandwidth product. 

As a sidebar, the correct interpretaion of measurement in QM seems to be disputed, though that discussion is beyond my pay grade. I believe Roger Penrose has a new book coming out that challenges some current orthodoxy.  See a recent interview in Discover.  Also, I&#039;m wondering how the points on deterministic signals apply to fractals.  But that&#039;s a different topic. 

Thanks for the enlightment and the blog.</description>
		<content:encoded><![CDATA[<p>I see your point.  The standard interpretation of the uncertainty principle seems to be that the inability to measure inverse quantities simultaneously is a property of the system itself, not the measurement device, which is not true for deterministic signals.  By contrast, my analogy (not an exact one) pertains to how the measurement is mathematically made with a particular phase-space distribution.  The connection is that both ultimately stem from the time-bandwidth product. </p>
<p>As a sidebar, the correct interpretaion of measurement in QM seems to be disputed, though that discussion is beyond my pay grade. I believe Roger Penrose has a new book coming out that challenges some current orthodoxy.  See a recent interview in Discover.  Also, I&#8217;m wondering how the points on deterministic signals apply to fractals.  But that&#8217;s a different topic. </p>
<p>Thanks for the enlightment and the blog.</p>
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		<title>Comment on Phase-space optics 1: Introduction by Shalin Mehta</title>
		<link>http://shalin.wordpress.com/2009/09/07/thoughts-on-phase-space-optics-1/#comment-79</link>
		<dc:creator>Shalin Mehta</dc:creator>
		<pubDate>Wed, 07 Oct 2009 04:28:34 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=237#comment-79</guid>
		<description>&lt;blockquote&gt;
The analogy to quantum may be more apt than you indicate. Mind you, I’m not certain, but here is my interpretation. The uncertainty principle implies that certain properties cannot be measured simultaneously to arbitrary accuracy, not they can’t be measured to arbitrary accuracy individually by separate probes. Right?&lt;/blockquote&gt;

I think that as far as signal analysis is concerned, one can measure both time features and frequency features to better accuracy than uncertainty principle. I am not familiar with quantum mechanical methods of measuring position and momentum simultaneously, so find it hard to visualize what aspect limits the resolution of measurement. The limit on signal measurement will be imposed by capabilities of the measurement instrument. Following example comes to mind: Capture a signal at very high sampling-rate using the best A2D converter and then compute a continuous wavelet transform or continuous wigner distribution in the other dimension. However, if we compare the time-width and band-width from this measurement and analysis, we will find that their product cannot be smaller than uncertainty limit. Thus, the uncertainty principle limits the time-bandwidth product of a signal rather than its measurement. One may think of making the above distinction as pedantic but it seems an important conceptual difference to me.

&lt;blockquote&gt; Also, all squared phase-space decompositions like a wavelet scalogram can be shown to be a phase-space averaging of the Wigner-Ville with a smoothing kernel. In support of your interpretation the WVD does, however, satisfy phase and space marginal integrals (integrating wrt phase gives the square of the spatial distribution and vice versa), but the WVD is not strictly positive due to interference terms. In fact, it has been shown that no positive quadratic energy distribution can satisfy the marginal integrals. The required smoothing that reduces phase-space resolution seems to bear some resemblance to the uncertainty principle in QM. &lt;/blockquote&gt;

This is a very interesting point, viz., all physically meaningful distributions are related to Wigner distribution with a smoothing kernel. As an example, we find that the phase-space representation of partially coherent imaging systems is a convolution of the specimen&#039;s Wigner distribution with a kernel dependent on the imaging system&#039;s parameters (illumination and imaging pupils). This is the topic of my talk on Monday at FiO. I think of this situation as implying that signal obtained from a physical system has larger or at best the same time-bandwidth product as obtained with Wigner distribution.</description>
		<content:encoded><![CDATA[<blockquote><p>
The analogy to quantum may be more apt than you indicate. Mind you, I’m not certain, but here is my interpretation. The uncertainty principle implies that certain properties cannot be measured simultaneously to arbitrary accuracy, not they can’t be measured to arbitrary accuracy individually by separate probes. Right?</p></blockquote>
<p>I think that as far as signal analysis is concerned, one can measure both time features and frequency features to better accuracy than uncertainty principle. I am not familiar with quantum mechanical methods of measuring position and momentum simultaneously, so find it hard to visualize what aspect limits the resolution of measurement. The limit on signal measurement will be imposed by capabilities of the measurement instrument. Following example comes to mind: Capture a signal at very high sampling-rate using the best A2D converter and then compute a continuous wavelet transform or continuous wigner distribution in the other dimension. However, if we compare the time-width and band-width from this measurement and analysis, we will find that their product cannot be smaller than uncertainty limit. Thus, the uncertainty principle limits the time-bandwidth product of a signal rather than its measurement. One may think of making the above distinction as pedantic but it seems an important conceptual difference to me.</p>
<blockquote><p> Also, all squared phase-space decompositions like a wavelet scalogram can be shown to be a phase-space averaging of the Wigner-Ville with a smoothing kernel. In support of your interpretation the WVD does, however, satisfy phase and space marginal integrals (integrating wrt phase gives the square of the spatial distribution and vice versa), but the WVD is not strictly positive due to interference terms. In fact, it has been shown that no positive quadratic energy distribution can satisfy the marginal integrals. The required smoothing that reduces phase-space resolution seems to bear some resemblance to the uncertainty principle in QM. </p></blockquote>
<p>This is a very interesting point, viz., all physically meaningful distributions are related to Wigner distribution with a smoothing kernel. As an example, we find that the phase-space representation of partially coherent imaging systems is a convolution of the specimen&#8217;s Wigner distribution with a kernel dependent on the imaging system&#8217;s parameters (illumination and imaging pupils). This is the topic of my talk on Monday at FiO. I think of this situation as implying that signal obtained from a physical system has larger or at best the same time-bandwidth product as obtained with Wigner distribution.</p>
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		<title>Comment on Phase-space optics 1: Introduction by S. Barwick</title>
		<link>http://shalin.wordpress.com/2009/09/07/thoughts-on-phase-space-optics-1/#comment-76</link>
		<dc:creator>S. Barwick</dc:creator>
		<pubDate>Tue, 06 Oct 2009 18:12:36 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=237#comment-76</guid>
		<description>&quot;Straightforward extrapolation of the uncertainty principle from quantum mechanics to signal analysis may suggest that one cannot measure the instantaneous spectrum with high temporal resolution. Though plausible, this is not the correct interpretation – for whatever the definition of instantaneous spectrum, one can compute it to arbitrary accuracy since the signal is deterministic.&quot;

The analogy to quantum may be more apt than you indicate.  Mind you, I&#039;m not certain, but here is my interpretation.  The uncertainty principle implies that certain properties cannot be measured simultaneously to arbitrary accuracy, not they can&#039;t be measured to arbitrary accuracy individually by separate probes. Right? 

Wavelets are a type of phase-space distribution, for example.  Individual wavelet atoms are generally interpreted as covering a certain panel in the phase-space plane (1-D signals).  A wavelet that is localized in space and, thus, provides precise spatial information, will have a broad spectrum and vice versa.  Thus, the chosen phase-space probe will in fact be subject to a restriction akin to the uncertainty principle.  

Also, all squared phase-space decompositions like a wavelet scalogram can be shown to be a phase-space averaging of the Wigner-Ville with a smoothing kernel.  In support of your interpretation the WVD does, however, satisfy phase and space marginal integrals (integrating wrt phase gives the square of the spatial distribution and vice versa), but the WVD is not strictly positive due to interference terms.  In fact, it has been shown that no positive quadratic energy distribution can satisfy the marginal integrals.  The required smoothing that reduces phase-space resolution seems to bear some resemblance to the uncertainty principle in QM.</description>
		<content:encoded><![CDATA[<p>&#8220;Straightforward extrapolation of the uncertainty principle from quantum mechanics to signal analysis may suggest that one cannot measure the instantaneous spectrum with high temporal resolution. Though plausible, this is not the correct interpretation – for whatever the definition of instantaneous spectrum, one can compute it to arbitrary accuracy since the signal is deterministic.&#8221;</p>
<p>The analogy to quantum may be more apt than you indicate.  Mind you, I&#8217;m not certain, but here is my interpretation.  The uncertainty principle implies that certain properties cannot be measured simultaneously to arbitrary accuracy, not they can&#8217;t be measured to arbitrary accuracy individually by separate probes. Right? </p>
<p>Wavelets are a type of phase-space distribution, for example.  Individual wavelet atoms are generally interpreted as covering a certain panel in the phase-space plane (1-D signals).  A wavelet that is localized in space and, thus, provides precise spatial information, will have a broad spectrum and vice versa.  Thus, the chosen phase-space probe will in fact be subject to a restriction akin to the uncertainty principle.  </p>
<p>Also, all squared phase-space decompositions like a wavelet scalogram can be shown to be a phase-space averaging of the Wigner-Ville with a smoothing kernel.  In support of your interpretation the WVD does, however, satisfy phase and space marginal integrals (integrating wrt phase gives the square of the spatial distribution and vice versa), but the WVD is not strictly positive due to interference terms.  In fact, it has been shown that no positive quadratic energy distribution can satisfy the marginal integrals.  The required smoothing that reduces phase-space resolution seems to bear some resemblance to the uncertainty principle in QM.</p>
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		<title>Comment on Impressive 3D optical illusion by Shalin Mehta</title>
		<link>http://shalin.wordpress.com/2009/08/18/impressive-3d-optical-illusion/#comment-75</link>
		<dc:creator>Shalin Mehta</dc:creator>
		<pubDate>Wed, 30 Sep 2009 23:47:30 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=202#comment-75</guid>
		<description>Very interesting! Thanks for sharing this link. I couldn&#039;t believe two images of the leaning tower were the same. It points out that we do not directly perceive depth, but infer it using visual cues based on some rules. I wonder how do we learn these rules in the first place and could we learn the exceptions too? Perfect question to ask at FiO.</description>
		<content:encoded><![CDATA[<p>Very interesting! Thanks for sharing this link. I couldn&#8217;t believe two images of the leaning tower were the same. It points out that we do not directly perceive depth, but infer it using visual cues based on some rules. I wonder how do we learn these rules in the first place and could we learn the exceptions too? Perfect question to ask at FiO.</p>
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		<title>Comment on &#8216;Prepone&#8217; doesn&#8217;t exist in dictionary!!? by Dan Franzen</title>
		<link>http://shalin.wordpress.com/2008/08/26/preponed-doesnt-exist-in-dictionary/#comment-73</link>
		<dc:creator>Dan Franzen</dc:creator>
		<pubDate>Wed, 30 Sep 2009 19:52:59 +0000</pubDate>
		<guid isPermaLink="false">http://shalin.wordpress.com/?p=42#comment-73</guid>
		<description>I suppose it&#039;s not used in American English because &quot;postpone&quot; is used specifically to indicate that something is being forestalled, i.e., put off or put into the future; it&#039;s a little difficult to move backwards in the time-space continuum.</description>
		<content:encoded><![CDATA[<p>I suppose it&#8217;s not used in American English because &#8220;postpone&#8221; is used specifically to indicate that something is being forestalled, i.e., put off or put into the future; it&#8217;s a little difficult to move backwards in the time-space continuum.</p>
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