frecvenei

Frecvenei is a neologism used in discussions of temporal data to refer to a composite descriptor that captures both the frequency content of a signal and the persistence of repetitive patterns over time. In practice, frecvenei denotes a measure that combines spectral components with a recurrence or stability metric, allowing analysts to describe not only which frequencies dominate, but also how consistently those patterns recur across successive intervals. The term does not have a single, official definition and its usage varies among authors; it is not part of formal standards in signal processing.

The etymology is not standardized. It appears as a portmanteau blending elements of "frequency" with a plural suffix, used informally to denote a concept rather than a specific algorithm.

In computation, frecvenei can be estimated by first performing a spectral decomposition to identify frequency content, then applying a recurrence analysis—such as autocorrelation, delay-embedding, or recurrence plots—to assess how repeating patterns persist across time. The resulting frecvenei score may be scalar or multi-dimensional, representing both spectral power and recurrence strength.

Frecvenei has been discussed in contexts ranging from theoretical signal modeling to music information retrieval and exploratory neuroscience; in each case, it is treated as a heuristic rather than an established standard. Practitioners should be mindful of sensitivity to noise, window length, and sampling rate, and should validate frecvenei findings against established methods.

See also: frequency analysis, time-series analysis, recurrence plots.