The capacity of a binary symmetric channel, given H(P) is binary entropy function, is
a) 1-H(P) b) H(P)-1 c) 1-H(P)2 d) H(P)2-1
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p = probability of success of sending bit over the channel.
The binary Entropy function = H(p)
![H(p)=-Log_2\ [ p^p\ (1-p)^{1-p} ] H(p)=-Log_2\ [ p^p\ (1-p)^{1-p} ]](https://tex.z-dn.net/?f=H%28p%29%3D-Log_2%5C+%5B+p%5Ep%5C+%281-p%29%5E%7B1-p%7D+%5D)
For a binary symmetric channel: Capacity C = 1 - H(p)
The binary Entropy function = H(p)
For a binary symmetric channel: Capacity C = 1 - H(p)
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The capacity of a binary symmetric channel, given H(P) is binary entropy function, is a) 1-H(P)
Explanation:
- The channel capacity of the binary symmetric channel is 1 H(p), where H (p) = p log p (1 p) log (1 p) is the Shannon entropy of a binary distribution with probability p and 1 p.
- The channel capacity of the erasure channel is p, where p is the chance that the transmitted bit is not erased.
- A binary symmetric channel is a communications channel model that is commonly used in coding theory and information theory. In this approach, the transmitter sends a bit (either a zero or a one), and the receiver receives a bit.
- #SPJ3
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