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_func
sending eachx : α
to the pointe k
which is the nearest tox
amonge 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 ins
and 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 x
asn
tends 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