Neblux Knowledge Graph

Information Theory

Information theory is the mathematical study of uncertainty, data encoding, and communication over channels.

Overview

Shannon’s 1948 framework measures statistical uncertainty, not meaning. For a discrete memoryless channel, suitable codes operating below capacity can make decoding error arbitrarily small as block length grows. This is a result under a specified model, not a promise of error-free finite messages.

Why it matters

In a study of fly vision, Strong and colleagues used entropy estimates to examine how spike timing conveys information about a moving stimulus. This connects a statistical information measure to experimental recordings, with conclusions tied to the stimulus and sampling choices.

Where it leads

• Publication of Shannon's Communication Theory

Related concepts

• MathematicslogicalInformation theory is built on probability theory and uses mathematical entropy as its central measure
• TechnologyappliedAll digital communication — the internet, compression, error correction — is built on information theory
• ThermodynamicsconceptualShannon entropy is mathematically identical in form to thermodynamic entropy, connecting information and physics