pith. sign in
module module moderate

IndisputableMonolith.Analysis.BernsteinInequality

show as:
view Lean formalization →

The BernsteinInequality module defines frequency-bounded functions and their derivative bounds in Recognition Science. It supplies FrequencyBounded, BernsteinBound, amplitude sums, and BernsteinCert using the time quantum from Constants. The module consists of definitions plus elementary nonnegativity lemmas.

claimFrequencyBounded$(f,\omega)$ asserts a function $f$ has frequency support at most $\omega$ (in units with $\tau_0=1$). BernsteinBound$(f,\omega)$ states $\|f'\|\leq\omega\|f\|$. BernsteinCert witnesses the bound via amplitude_sum and derivative_amplitude_sum.

background

The module sits in the Analysis domain and imports the RS time quantum $\tau_0=1$ tick from IndisputableMonolith.Constants. It introduces FrequencyBounded, amplitude_sum, derivative_amplitude_sum, and derivative_bounded_by_frequency to set up the classical Bernstein inequality inside RS-native units.

No module-level doc comment is supplied. The sibling declarations establish nonnegativity of the bounds and existence of a certificate, all resting on the imported constant.

proof idea

This is a definition module, no proofs.

why it matters in Recognition Science

The module supplies the Bernstein inequality primitives that feed into parent theorems on wave propagation and frequency analysis within the Recognition framework. It fills the analysis layer required before mass-ladder or J-cost constructions that rely on bounded derivatives.

scope and limits

depends on (1)

Lean names referenced from this declaration's body.

declarations in this module (10)