Computer science
Information theory
Information content, entropy and alphabet encoding.
Computer science
Hartley information
I = log₂N→Computer scienceSelf-information
I = −log₂p→Computer scienceBinary entropy
H = −p log₂p − (1−p)log₂(1−p)→Computer scienceMessage information from alphabet
I = K log₂N→Computer scienceMinimum fixed code length
b = ⌈log₂N⌉→Computer scienceMaximum entropy
Hmax = log₂N→Computer scienceCode redundancy
D = 1 − H / Hmax→Computer scienceHamming parity bits
2ʳ ≥ m + r + 1→Computer scienceCodeword length
n = m + r→