An Introduction to Information Theory: Symbols, Signals and Noise
E75861
An Introduction to Information Theory: Symbols, Signals and Noise is a classic, accessible textbook that explains the fundamental concepts of information theory, communication, and coding for a broad scientific and engineering audience.
All labels observed (1)
| Label | Occurrences |
|---|---|
| An Introduction to Information Theory: Symbols, Signals and Noise canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T608256 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: An Introduction to Information Theory: Symbols, Signals and Noise Context triple: [John R. Pierce, notableWork, An Introduction to Information Theory: Symbols, Signals and Noise]
-
A.
A Mathematical Theory of Communication
A Mathematical Theory of Communication is Claude Shannon’s landmark 1948 paper that founded information theory by rigorously defining concepts like information, entropy, and channel capacity.
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B.
Communication Theory of Secrecy Systems
Communication Theory of Secrecy Systems is Claude Shannon’s foundational paper that established the mathematical basis of modern cryptography and information-theoretic security.
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C.
Shannon–Khinchin axioms
The Shannon–Khinchin axioms are a set of fundamental conditions that uniquely characterize Shannon entropy as the standard measure of information and uncertainty in probability theory and information theory.
-
D.
Shannon entropy
Shannon entropy is a fundamental measure in information theory that quantifies the average uncertainty or information content in a random variable or message source.
-
E.
Introduction to the Theory of Computation
Introduction to the Theory of Computation is a widely used textbook in theoretical computer science that covers formal languages, automata, computability, and complexity theory.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: An Introduction to Information Theory: Symbols, Signals and Noise Target entity description: An Introduction to Information Theory: Symbols, Signals and Noise is a classic, accessible textbook that explains the fundamental concepts of information theory, communication, and coding for a broad scientific and engineering audience.
-
A.
A Mathematical Theory of Communication
A Mathematical Theory of Communication is Claude Shannon’s landmark 1948 paper that founded information theory by rigorously defining concepts like information, entropy, and channel capacity.
-
B.
Communication Theory of Secrecy Systems
Communication Theory of Secrecy Systems is Claude Shannon’s foundational paper that established the mathematical basis of modern cryptography and information-theoretic security.
-
C.
Shannon–Khinchin axioms
The Shannon–Khinchin axioms are a set of fundamental conditions that uniquely characterize Shannon entropy as the standard measure of information and uncertainty in probability theory and information theory.
-
D.
Shannon entropy
Shannon entropy is a fundamental measure in information theory that quantifies the average uncertainty or information content in a random variable or message source.
-
E.
Introduction to the Theory of Computation
Introduction to the Theory of Computation is a widely used textbook in theoretical computer science that covers formal languages, automata, computability, and complexity theory.
- F. None of above. chosen
Statements (39)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
textbook ⓘ |
| audience |
engineers
ⓘ
scientists ⓘ students ⓘ |
| author | John R. Pierce ⓘ |
| covers |
Shannon’s theory of communication
ⓘ
linked to:
A Mathematical Theory of Communication
channel capacity ⓘ error detection and correction concepts ⓘ measurement of information ⓘ redundancy in messages ⓘ |
| field |
coding theory
ⓘ
communication theory ⓘ information theory ⓘ |
| focus | conceptual understanding rather than heavy mathematics ⓘ |
| genre | non-fiction ⓘ |
| hasPart |
noise
ⓘ
signals ⓘ symbols ⓘ |
| intendedUse |
self-study
ⓘ
university-level course text ⓘ |
| language | English ⓘ |
| reputation | classic text in information theory ⓘ |
| subjectArea |
applied mathematics
ⓘ
computer science ⓘ electrical engineering ⓘ |
| teaches |
basic concepts of information theory
ⓘ
mathematical description of information ⓘ principles of coding for reliable communication ⓘ role of noise in communication ⓘ |
| topic |
coding and codes
ⓘ
communication channels ⓘ data transmission ⓘ entropy ⓘ information ⓘ noise in communication systems ⓘ probability in communication ⓘ |
| writingStyle |
accessible
ⓘ
introductory ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: An Introduction to Information Theory: Symbols, Signals and Noise Description of subject: An Introduction to Information Theory: Symbols, Signals and Noise is a classic, accessible textbook that explains the fundamental concepts of information theory, communication, and coding for a broad scientific and engineering audience.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.