Does this help?

Yeah, but how increasing the freq. increase the energy??

Then he plays a note 1 octave higher, but not any louder, such that it is given by:

& what is this 1 octane??

 

Yeah, but how increasing the freq. increase the energy??

This is a fundamental property of the universe. We see this everywhere. In light:

\(E\ =\ h\nu \ \ \ \ where \ \nu\ is\ the\ frequency\)

And in a vibrating string, energy, at a fixed amplitude, is proportional to the square of the frequency.

Try shaking your hand back and forth once a second, then try to do it the same distance twice a second. You will see it takes much more effort. Basically when things move faster they have more energy.

& what is this 1 octane??

One octave is a change in pitch of a factor of 2. One octave higher is twice the frequency, one octave lower is half the frequency.

 

Many of these concepts apply for music in a practical way. The general theory is good for RF and beyond.

 

Hi again,
what is the use of convolution theorem in freq. & time domain practical??

 

I don't know what convolution theorem is, but think in terms of RMS. The RMS of a square wave is 1 * Peak volts of the wave form. The RMS of a sine wave is 0.707 * Peak volts of the wave form. A square wave delivers more energy.

 

RRITESH,

I have to ask, is this leading somewhere? It seems you are just asking questions surrounding some of the consequences of the Fourier transform.

Scaling is one thing. It at least has some easy to realize applications, but the convolution theorem is very esoteric. Is there a particular place you are going with this? It might help to know that.

The reason I ask is that its going to be difficult to give 'easy' examples of convolution theorem. So, the second question I have for you is, do you understand what mathematical convolution is?

 

Many of these concepts apply for music in a practical way. The general theory is good for RF and beyond.

They even apply to non-periodic functions, but it's so hard to provide easy to understand examples for them. Sometimes it is better to just learn the math for its own sake without thinking how it applies to the real world. The bulk of mathematics has no real world application. It's just math.

 

I have to ask, is this leading somewhere? It seems you are just asking questions surrounding some of the consequences of the Fourier transform.

Scaling is one thing. It at least has some easy to realize applications, but the convolution theorem is very esoteric. Is there a particular place you are going with this? It might help to know that.


The reason I ask is that its going to be difficult to give 'easy' examples of convolution theorem. So, the second question I have for you is, do you understand what mathematical convolution is?

Hi again,

Yes, it is in my course book, please tell from starting what need of it in real world??


Thanks.

 

There are a lot of examples of convolution and the convolution theorem. Here are some links you might enjoy:

http://en.wikipedia.org/wiki/Convolution
http://en.wikipedia.org/wiki/Convolution_theorem
http://www-structmed.cimr.cam.ac.uk/Course/Convolution/convolution.html

 

hi,

in this animation http://en.wikipedia.org/wiki/Convolution
Shows triangular wave how when both are square wave ??

& in second pics. it shows Impulse, as i know impulse is a small width pulse like rectangular, but here is different.

 

hi,

in this animation http://en.wikipedia.org/wiki/Convolution
Shows triangular wave how when both are square wave ??

It is explained under the animation. The triangle is a plot of the overlap area (amount of yellow) as the two functions f and g cross each other. This is the convolution f*g.

& in second pics. it shows Impulse, as i know impulse is a small width pulse like rectangular, but here is different.

Again, this is explained below the animation. The function f is not an impulse, it is the response to an impulse by and RC circuit.

 

The triangle is a plot of the overlap area (amount of yellow) as the two functions f and g cross each other. This is the convolution f*g.

Why there come triangle is it is in Freq. or time domain??

 

Why there come triangle is it is in Freq. or time domain??

Since this has not undergone Fourier transformation yet, it is in the time domain.

 

Why there come triangle only not sq. or other??

 

reply............

 

Rritesh, you need to look at the animations and think about what is happening. Look at the amount of overlap between the square pulses as they cross each other. This is rather obvious. If you can't figure this out, you might be in the wrong subject.

Sorry if that sounds harsh, but you need to do some of your own thinking.

 

going, through it i think the yellow curve starts from middle of sq. wave to linear slope cont. the decrease linearly it is freq. domain of it??

 

This has nothing to do with the frequency domain. I can not try to explain to you about applications of the convolution theorem until you understand convolution. So, this animation is just a demonstration of the convolution in the time domain between two square pulses. That convolution is the triangle, which is essentially a function of the overlap of the two square pulses. Do you see that?

 

It is the area in the overlap of the two square pulses (going with the animation).

 

Thanks, member for the help today my exam was over...!!

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