Shannon's capacity formular

  • Thread starter persist911
  • Start date
  • Tags
    Capacity
In summary, The conversation was about the Shannon capacity formula and its proof using a n-hyperspace of uncertainty. One problem mentioned was understanding the concept of modeling signals and noise as circles and the requirement for the spheres of uncertainty to not overlap. The other problem was understanding the Nyquist sampling theorem and its relationship with frequency and time concepts. The speaker also mentioned confusion about aliasing and the Nyquist sample frequency.
  • #1
persist911
8
0
I was in taught howw to proves the shannons capacity formula using by takng into conideration a n-hyperspace of uncertanity where the noise resides. It more like the geomteric proof of Shannon formula

c = b*log(1+s/n)
I have two problems
1) he modeled signals like a round circle and noise around it like a round circle. and he said the sphere of uncertanity must not overlap. Is it more like a wireless networks with noise around the environment? I did like an insight into this proof

2) I don't seem to understand the Nyquist sampling theorem of n=2BT it is like the concepts of frequency has been Muddled Up with the perioid. I know the realtionship between frequency f = 1/t but when sampled time concepts come into play I am confused could anyone shed more light on this.

Thanks I am sorry my question is kind of long .
 
Engineering news on Phys.org
  • #2
persist911 said:
2) I don't seem to understand the Nyquist sampling theorem of n=2BT it is like the concepts of frequency has been Muddled Up with the perioid. I know the realtionship between frequency f = 1/t but when sampled time concepts come into play I am confused could anyone shed more light on this.

You must have missed the idea of aliasing, and thus the Nyquist sample frequency. https://en.wikipedia.org/wiki/Nyquist_frequency
 

Related to Shannon's capacity formular

What is Shannon's capacity formula?

Shannon's capacity formula, also known as the Shannon-Hartley theorem, is a mathematical equation developed by Claude Shannon in 1948. It determines the maximum rate at which information can be transmitted over a communication channel with a specific bandwidth and level of noise.

How is Shannon's capacity formula calculated?

The formula is C = B log2(1 + S/N), where C is the channel capacity in bits per second, B is the bandwidth in hertz, and S/N is the signal-to-noise ratio. This formula assumes a noiseless channel, but can be modified to include the effects of noise.

What is the significance of Shannon's capacity formula?

Shannon's capacity formula is significant because it provides a theoretical limit for the amount of information that can be reliably transmitted over a communication channel. It is used in the design and optimization of communication systems, such as wireless networks and optical fibers.

What factors can affect Shannon's capacity?

Shannon's capacity can be affected by the bandwidth of the channel, the level of noise present, and the signal-to-noise ratio. Other factors that can impact the capacity include the modulation scheme, coding techniques, and channel impairments such as fading and interference.

Can Shannon's capacity formula be used in practical applications?

Yes, Shannon's capacity formula is widely used in practical applications, especially in the field of telecommunications. It is used to determine the maximum data rate that can be transmitted over a channel, and is used in the design and optimization of communication systems to ensure efficient and reliable transmission of information.

Similar threads

Replies
7
Views
3K
Replies
9
Views
1K
Replies
4
Views
2K
Replies
4
Views
6K
  • Electrical Engineering
Replies
8
Views
7K
  • Electrical Engineering
Replies
1
Views
10K
Replies
12
Views
998
  • Classical Physics
Replies
8
Views
2K
  • Introductory Physics Homework Help
Replies
2
Views
4K
  • Precalculus Mathematics Homework Help
Replies
2
Views
2K
Back
Top