Density of simple functions #
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Show that each Borel measurable function can be approximated pointwise by a sequence of simple functions.
Main definitions #
measure_theory.simple_func.nearest_pt (e : ℕ → α) (N : ℕ) : α →ₛ ℕ: thesimple_funcsending eachx : αto the pointe kwhich is the nearest toxamonge 0, ...,e N.measure_theory.simple_func.approx_on (f : β → α) (hf : measurable f) (s : set α) (y₀ : α) (h₀ : y₀ ∈ s) [separable_space s] (n : ℕ) : β →ₛ α: a simple function that takes values insand approximatesf.
Main results #
tendsto_approx_on(pointwise convergence): Iff x ∈ s, then the sequence of simple approximationsmeasure_theory.simple_func.approx_on f hf s y₀ h₀ n, evaluated atx, tends tof xasntends to∞.
Notations #
α →ₛ β(local notation): the type of simple functionsα → β.
Pointwise approximation by simple functions #
nearest_pt_ind e N x is the index k such that e k is the nearest point to x among the
points e 0, ..., e N. If more than one point are at the same distance from x, then
nearest_pt_ind e N x returns the least of their indexes.
Equations
- measure_theory.simple_func.nearest_pt_ind e (N + 1) = measure_theory.simple_func.piecewise (⋂ (k : ℕ) (H : k ≤ N), {x : α | has_edist.edist (e (N + 1)) x < has_edist.edist (e k) x}) _ (measure_theory.simple_func.const α (N + 1)) (measure_theory.simple_func.nearest_pt_ind e N)
- measure_theory.simple_func.nearest_pt_ind e 0 = measure_theory.simple_func.const α 0
nearest_pt e N x is the nearest point to x among the points e 0, ..., e N. If more than
one point are at the same distance from x, then nearest_pt e N x returns the point with the
least possible index.
Approximate a measurable function by a sequence of simple functions F n such that
F n x ∈ s.
Equations
- measure_theory.simple_func.approx_on f hf s y₀ h₀ n = (measure_theory.simple_func.nearest_pt (λ (k : ℕ), k.cases_on y₀ (coe ∘ topological_space.dense_seq ↥s)) n).comp f hf