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Relation of Lagrange and Sinc Interpolation
For an infinite number of equally spaced
samples, with spacing
, the Lagrangian basis
polynomials converge to shifts of the sinc function, i.e.,
where
sinc
A simple argument is based on the fact that any analytic function is
determined by its zeros and its value at one point. Since
sinc

is zero on all the integers except 0, and since
sinc

, it
must coincide with the infinite-order Lagrangian basis polynomial for
the sample at

which also has its zeros on the nonzero integers
and equals

at

.
The equivalence of sinc interpolation to Lagrange interpolation was
apparently first published by the mathematician Borel in 1899, and has
been rediscovered many times since [318, p. 325].
A direct proof can be based on the equivalance between Lagrange
interpolation and windowed-sinc interpolation using a ``binomial
window'' [269,515]. That is, for a
fractional sample delay of
samples, multiply the shifted-by-
,
sampled, sinc function

sinc
by a binomial window
and normalize by [
515]
which normalizes the interpolating
filter to have a unit
norm, to
obtain the

th-order Lagrange interpolating filter
Since the binomial window converges to the
Gaussian window as

,
and since the window gets wider and wider, approaching a unit constant in
the limit, the convergence of Lagrange to sinc interpolation can be seen.
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Lagrange InterpolationNext:
Lagrange Interpolation Optimality
written by Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at
Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See
http://ccrma.stanford.edu/~jos/ for details.