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In mathematics, the question of whether the Fourier series of a given periodic function converges to the given function is researched by a field known as classical harmonic analysis, a branch of pure mathematics. Convergence is not necessarily given in the general case, and certain criteria must be met for convergence to occur.
This was disproved by Paul du Bois-Reymond, who showed in 1876 that there is a continuous function whose Fourier series diverges at one point. The almost-everywhere convergence of Fourier series for L 2 functions was postulated by N. N. Luzin , and the problem was known as Luzin's conjecture (up until its proof by Carleson (1966)).
A version holds for Fourier series as well: if is an integrable function on a bounded interval, then the Fourier coefficients ^ of tend to 0 as . This follows by extending f {\displaystyle f} by zero outside the interval, and then applying the version of the Riemann–Lebesgue lemma on the entire real line.
The theorems proving that a Fourier series is a valid representation of any periodic function (that satisfies the Dirichlet conditions), and informal variations of them that don't specify the convergence conditions, are sometimes referred to generically as Fourier's theorem or the Fourier theorem.
The convolution of D n (x) with any function f of period 2 π is the nth-degree Fourier series approximation to f, i.e., we have () = () = = ^ (), where ^ = is the k th Fourier coefficient of f. This implies that in order to study convergence of Fourier series it is enough to study properties of the Dirichlet kernel.
Then the Fourier series of f converges at t to f(t). For example, the theorem holds with ω f = log −2 ( 1 / δ ) but does not hold with log −1 ( 1 / δ ). Theorem (the Dini–Lipschitz test): Assume a function f satisfies = ().
There exist many types of convergence for a function series, such as uniform convergence, pointwise convergence, and convergence almost everywhere.Each type of convergence corresponds to a different metric for the space of functions that are added together in the series, and thus a different type of limit.
The trade-off between the compaction of a function and its Fourier transform can be formalized in the form of an uncertainty principle by viewing a function and its Fourier transform as conjugate variables with respect to the symplectic form on the time–frequency domain: from the point of view of the linear canonical transformation, the ...