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In number theory, a branch of mathematics, the Carmichael function λ(n) of a positive integer n is the smallest positive integer m such that holds for every integer a coprime to n. In algebraic terms, λ(n) is the exponent of the multiplicative group of integers modulo n. The Carmichael function is named after the American mathematician Robert Carmichael who defined it in 1910. It is also known as Carmichael's λ function, the reduced totient function, and the least universal exponent function. The following table compares the first 36 values of λ(n) with Euler's totient function φ (in bold if they are different; the ns such that they are different are listed in ). Carmichael's function at 5 is 4, λ(5) = 4, because for any number coprime to 5, i.e. there is with namely, 11⋅4 = 14 ≡ 1 (mod 5), 24 = 16 ≡ 1 (mod 5), 34 = 81 ≡ 1 (mod 5) and 42⋅2 = 162 ≡ 12 (mod 5). And this m = 4 is the smallest exponent with this property, because (and as well.)Moreover, Euler's totient function at 5 is 4, φ(5) = 4, because there are exactly 4 numbers less than and coprime to 5 (1, 2, 3, and 4). Euler's theorem assures that a4 ≡ 1 (mod 5) for all a coprime to 5, and 4 is the smallest such exponent. Carmichael's function at 8 is 2, λ(8) = 2, because for any number a coprime to 8, i.e. it holds that a2 ≡ 1 (mod 8). Namely, 11⋅2 = 12 ≡ 1 (mod 8), 32 = 9 ≡ 1 (mod 8), 52 = 25 ≡ 1 (mod 8) and 72 = 49 ≡ 1 (mod 8).Euler's totient function at 8 is 4, φ(8) = 4, because there are exactly 4 numbers less than and coprime to 8 (1, 3, 5, and 7). Moreover, Euler's theorem assures that a4 ≡ 1 (mod 8) for all a coprime to 8, but 4 is not the smallest such exponent. By the unique factorization theorem, any n > 1 can be written in a unique way as where p1 < p2 < ... < pk are primes and r1, r2, ..., rk are positive integers. Then λ(n) is the least common multiple of the λ of each of its prime power factors: This can be proved using the Chinese remainder theorem.
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will implement a simple fractional resampler that
uses local Lagrange interpolation. The resampler can be used to perform
any rational sampling rate change (but beware of aliasing when
downsampling!)
In [1]:
import numpy as np
import IPython
from scipy.io import wavfile
Local Lagrange interpolation[4]¶
To perform resampling we will need to compute subsample values and, in