lInformation

Linformation is a term used to describe the information content associated with a one-dimensional structure, such as a sequence, a time series, or a linear network edge. It is not a standard concept in established information theory, but it appears in niche discussions and proposals to emphasize information that is carried along a line rather than in a two- or three-dimensional arrangement.

Two common interpretations are used in vaguely defined contexts. One views linformation as information density along a line, i.e., the average information per element in a sequence, equivalent in spirit to the entropy rate of a stochastic process. The other treats linformation as the total information content of a finite linear segment, obtained by summing the self-information of each symbol (i.e., the negative logarithm of its probability).

Applications are hypothetical or exploratory, including analysis of data transmitted over linear media (such as optical fibers or cables), information flow in time-series data, and the study of spatial data arranged along a line (for example sensor arrays or line graphs). In visualization or data science, linformation can refer to how information is distributed along a plotted line and where uncertainty is reduced most effectively.

Because the term is not standardized, its precise meaning depends on the context and explicit definitions. Readers should rely on formal definitions, such as entropy rate or information content, when comparing results labeled as linformation.