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The slecture was structured really well and that made it easy to follow and understand. The graphs really help demonstrate the ideas that are being conveyed. The only thing you might want to add, like a previous commenter said, would be to state what Nyquist is. | The slecture was structured really well and that made it easy to follow and understand. The graphs really help demonstrate the ideas that are being conveyed. The only thing you might want to add, like a previous commenter said, would be to state what Nyquist is. | ||
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| + | *Review by Chloe Kauffman | ||
| + | -I think it would be helpful if you add a little background as to what reconstruction of the signal entails. It is just a term assumed to be known and is used throughout the explanation. This would help tie some of the other topics together for this course. <br> | ||
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| + | -When you wrote "The frequency content of the original signal lies within the -π to π band. Therefore the signal can be properly reconstructed." For the above Nyquist sampling. I think it is a little unclear intuitively for the reader what conditions you are implying that you are meeting that make the reconstruction possible. For example, I'd add something about how this means there is no overlapping between repetitions which is why this -pi to pi band is important. You do that a little more at the very end after the below Nyquist sampling. | ||
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| + | But, overall this was explained well. I kind of skimmed over some of the math simplifications. The graphs were helpful. | ||
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Revision as of 01:11, 15 October 2014
Questions and Comments for DTFT of a Cosine Signal Sampled Above and Below the Nyquist Frequency
Please post your reviews, comments, and questions below.
- Review by Jacob Holtman
The work is very concise and easy to follow. In the introduction it might help to put a mathematical explanation of Nyquist, which is mentioned in the second section. Also color would help to distinguish the different sections of the plot and how when T is too small the parts seen between − p'iand <span class="texhtml" />pi comes from repetitions and not the initial transform k = 0.
- Review by Fabian Faes
The overall flow of the slecture is very easy to follow and understand. I thought the graphs and the accompanying explanations were very easy to follow and understand without too much difficulty. from my point of view I cannot think of something for improvement since I find the mathematics easy to understand and clearly explained. Great Job!
- Review by Botao Chen
Good job! Your demonstrations are easy to follow and your outlines are very clear. Is is a good reviewing material for me because of your use of graph which strongly support the demonstration. I could clear see what is going on when the Nyquist rule is violated and when it is not.
- Author answer here
- Review by Yerkebulan Y.
You clearly explained that if CT signal is sampled above Nyquist rate , there is no aliasing. And if it is below Nyquist rate there is aliasing, and original signal cannot be properly represented because frequencies do not lie between -pi and pi.
- Review by Randall Cochran
The slecture was structured really well and that made it easy to follow and understand. The graphs really help demonstrate the ideas that are being conveyed. The only thing you might want to add, like a previous commenter said, would be to state what Nyquist is.
- Review by Chloe Kauffman
-I think it would be helpful if you add a little background as to what reconstruction of the signal entails. It is just a term assumed to be known and is used throughout the explanation. This would help tie some of the other topics together for this course.
-When you wrote "The frequency content of the original signal lies within the -π to π band. Therefore the signal can be properly reconstructed." For the above Nyquist sampling. I think it is a little unclear intuitively for the reader what conditions you are implying that you are meeting that make the reconstruction possible. For example, I'd add something about how this means there is no overlapping between repetitions which is why this -pi to pi band is important. You do that a little more at the very end after the below Nyquist sampling.
But, overall this was explained well. I kind of skimmed over some of the math simplifications. The graphs were helpful.
