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Question

The entropy \(H\) of a source is equal to [...]:

\(\displaystyle H=\sum\limits^{N}_{i=1}p_{i}k_{i}=\sum\limits^{N}_{i=1}p_{i}\log_{2}(1/p_{i})\)

Answer
the expected (i.e. average) information content of its messages

Question

The entropy \(H\) of a source is equal to [...]:

\(\displaystyle H=\sum\limits^{N}_{i=1}p_{i}k_{i}=\sum\limits^{N}_{i=1}p_{i}\log_{2}(1/p_{i})\)

Answer
?

Question

The entropy \(H\) of a source is equal to [...]:

\(\displaystyle H=\sum\limits^{N}_{i=1}p_{i}k_{i}=\sum\limits^{N}_{i=1}p_{i}\log_{2}(1/p_{i})\)

Answer
the expected (i.e. average) information content of its messages
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Definition of Information Entropy
The entropy \(H\) of a source is equal to the expected (i.e. average) information content of its messages: \(\displaystyle H=\sum\limits^{N}_{i=1}p_{i}k_{i}=\sum\limits^{N}_{i=1}p_{i}\log_{2}(1/p_{i})\)

Summary

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

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