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Why DTFS uses only one period

Short answer

In continuous time, all harmonics e^{j k ω0 t} are distinct, requiring an infinite sum to represent signals with sharp transitions. In discrete time, e^{j (k+N) (2π/N) n} = e^{j k (2π/N) n}, so only N distinct harmonics exist; the series is a finite sum over one period.

A continuous time Fourier Series is evaluated over infinite duration while a discrete time Fourier series is evaluated over one time period only. Why?

The difference comes from how many distinct harmonics each signal can have:

  • Continuous time: the exponentials ejkω0te^{jk\omega_0 t} are all different for every integer kk; a higher kk is always a faster oscillation. A CT periodic signal (e.g. a square wave with sharp jumps) may need infinitely many harmonics, so the synthesis sum runs from k=−∞k = -\infty to ∞\infty, and convergence must be examined (Dirichlet conditions).
  • Discrete time: ej(k+N)(2π/N)n=ejk(2π/N)nej2πn=ejk(2π/N)ne^{j(k+N)(2\pi/N)n} = e^{jk(2\pi/N)n}e^{j2\pi n} = e^{jk(2\pi/N)n}, because nn is an integer. Only NN distinct exponentials exist, so both the synthesis and analysis sums need only one period (NN terms) and the coefficients repeat, ak+N=aka_{k+N} = a_k. The DTFS is a finite sum, so it always exists and has no convergence problem.

In both cases the analysis is done over one period of the signal; the "infinite" range in CT refers to the infinite number of harmonic terms needed.

✓ Answer checked by Claude Opus 5.5 (high effort)

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