inequality in information theory
C41080
concept
An inequality in information theory is a mathematical relation that bounds or compares information-theoretic quantities—such as entropy, mutual information, or divergence—to reveal fundamental limits on data compression, communication, and inference.
All labels observed (6)
| Label | Occurrences |
|---|---|
| bound on error probability | 1 |
| channel capacity theorem | 1 |
| coding theorem | 1 |
| inequality in information theory canonical | 1 |
| information theory theorem | 1 |
| information-theoretic inequality | 1 |
Description generation (CDg)
The one-sentence description above was generated by prompting gpt-5.1 with the class name and this instruction.
Instruction
generate a one-sentence description for a given conceptual class. # Response Format Return only the sentence: "Description: [one-sentence description of the conceptional class]"
Input
Class: inequality in information theory
Generated description
An inequality in information theory is a mathematical relation that bounds or compares information-theoretic quantities—such as entropy, mutual information, or divergence—to reveal fundamental limits on data compression, communication, and inference.
Instances (4)
| Instance | Via concept surface |
|---|---|
|
Mark Pinsker
surface form:
Pinsker's inequality
|
— |
| Fano inequality | information-theoretic inequality |
| Slepian–Wolf coding theorem | information theory theorem |
| Shannon–Hartley theorem | channel capacity theorem |