The Nyquist Limit can be disregarded as this is not a noiseless channel (faster signal = more noise, this channel's s/n ratio is provided as 20dB)
thus we use Shannon's result which says the maximum data rate of a noisy channel is X = H Log2 (1 + S/N) bps using 10Log10 S/N as our standard quality
2 = Log10 S/N --> S/N = 102 --> S/N = 100
X = 3000 Log2 (1 + 100) bps which gives you x = 19,974.63bps as your final answer.
~ Mike
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ALTERNATIVE APPROACHThe formula -
Shannon Capacity = Bandwidth * log2 ( 1 + Signal Power / Noise Power )
gets approximated to -
Shannon Capacity = Bandwidth * ( Signal to Noise ratio in dB ) / 3
assuming the fact that ....
Signal to Noise ratio in dB = 10 log10 ( Signal Power /Noise Power )
and also assuming
1 is much much less than Signal Power/Noise Power
So in the present case the approximate answer works out to
Shannon Capacity = Bandwidth * ( Signal to Noise ratio in dB ) / 3 ...
= 3KHz * 20 dB / 3
= 3 * 103 * 20 / 3 bits per second
= 20000 bits per second
~
ANIRUDDHA GHOSH
JADAVPUR UNIVERSITY
BSc Mathematics - 2004 - 2010
MCA - 2007 - 2010
~
The maximum height of a binary tree with 'n' nodes is 'n-1'.
The maximum number of comparisons required in a binary search algorithm to find a specific element in a sorted array is log(n), where n is the number of elements in the array.
To calculate the height of a binary tree, you can use a recursive algorithm that finds the maximum height of the left and right subtrees, and then adds 1 to the maximum height. This process is repeated for each node in the tree until the height of the entire tree is calculated.
The height of a binary search tree is the maximum number of edges from the root node to a leaf node. It represents the longest path from the root to a leaf in the tree.
To calculate the height of a binary tree, you can use a recursive algorithm that traverses the tree and keeps track of the height at each level. The height of a binary tree is the maximum depth of the tree, which is the longest path from the root to a leaf node.
The maximum height of a binary tree with 'n' nodes is 'n-1'.
255
Incomplete Binary Tree is a type of binary tree where we do not apply the following formula: 1. The Maximum number of nodes in a level is 2
Nyquist theorem for noiseless channel C= 2Blog22n. C= channel capacity in bps B= bandwidth in KHz 1 KHz= 1000 Hz C= 2*3*1000*log22. =6000 * log2 2. =6000 =6000 bps ..................................... Anu Chawla
+511
If we have a binary symmetric channel with an error probability Pe , then for error freecommunication over this channel, message from a source with entropy H(m) must be encoded by binary codes with a word length of at least H(m)/Cs whereCs = 1-[ Pe log(1/ Pe)+(1- Pe) log( ) ]The parameter Cs is called the channel capacity.Source: ewhatnhow.com/what-is-channel-capacity/
Plus or minus 65,535
36 hexadecimal and 24 binary sets.
The maximum number of comparisons required in a binary search algorithm to find a specific element in a sorted array is log(n), where n is the number of elements in the array.
To calculate the height of a binary tree, you can use a recursive algorithm that finds the maximum height of the left and right subtrees, and then adds 1 to the maximum height. This process is repeated for each node in the tree until the height of the entire tree is calculated.
The height of a binary search tree is the maximum number of edges from the root node to a leaf node. It represents the longest path from the root to a leaf in the tree.
To calculate the height of a binary tree, you can use a recursive algorithm that traverses the tree and keeps track of the height at each level. The height of a binary tree is the maximum depth of the tree, which is the longest path from the root to a leaf node.