Sampling Example

[@burakergocmen5661]

There is a lack of examples on web about sampling. It is very informative, thank you.

[@iain_explains]

Great. I'm glad it helped.

[@2002yeunglau]

Your Intuitive+mathematic explanation is so good.

[@iain_explains]

I’m glad you like it.

[@Pulsonar]

Very informative, I like the way you dive into the mathematics of it all as if its just tea and biscuits ;) As soon as maths notation comes into view Im done for. Im just thankful as an engineer I often figure problems and solutions from a practical perspective to 'cheat sheet' my way around the maths for most part, and my intuitive solution matches the final maths result. Good work.

[@tjcogger1974]

Very good video! How would you go about taking the inverse Fourier Transform of Y(jw) in part C?

[@iain_explains]

I'm not sure what you mean, sorry. It would just be a case of applying the definition of the inverse FT. Perhaps you are asking what the time domain waveform would actually look like? That's a good question. It would be a distorted version of a squared sinc function. It's a bit hard to explain in words, but it's a good topic for a future video.

[@HaSongSon123]

Hello Prof, why do we need to multiply with the factor 1/2pi in the frequency domain? In other books, i see that sometime this factor appears sometime not.

[@iain_explains]

When the Fourier transform is written/plotted in terms of angular frequency (omega) then the 2pi will appear, since omega = 2pi f .

[@KisoreMuthiahAnnamalai]

@@iain_explains But Sir why is this 2pi multiplied? What is the significance of doing so?

[@alparslan4871]

Please solve more examples about signals and systems

[@iain_explains]

Thanks for the suggestion. Do you have any particular topics in mind?

[@alparslan4871]

@@iain_explains LTI sytems as filters would be very helpful

[@iain_explains]

OK, I've added that topic to my list. Thanks.

[@mehdiamraoui8488]

i didnt understand why we get the constant at the end ..i mean the constant value .. can u plz explain ? thank u

[@iain_explains]

The final function is the summation of each of the component (offset) triangles (since the sampling function is a summation of offset delta functions). This means that at each frequency value (omega) you need to add the values of the component triangles that overlap with that frequency value (ie. that are non-zero for that frequency). Since the triangles have straight sides, the decreasing slope of one triangle is exactly matched by the increasing slope of the other overlapping triangle, so that the summation doesn't change for the range of frequencies where they overlap (and hence is results in a horizontal line , or a constant value, for that range of frequencies). Hope this helps.

[@sandhiyasahanapandiansamue1729]

Thank you so much Sir

[@iain_explains]

You're welcome. Glad it was helpful.