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Derive exponential Fourier series (CT)

Short answer

Synthesis: x(t)=∑ a_k e^(jkω0 t). Analysis: a_k = (1/T)∫_T x(t) e^(-jkω0 t) dt. Derived by multiplying synthesis by e^(-jnω0 t), integrating over one period T, and applying orthogonality: the integral of e^(j(k-n)ω0 t) is T for k=n, 0 otherwise.

Derive the exponential form of the Fourier series of a continuous-time periodic signal x(t) (synthesis and analysis equations).

A continuous-time periodic signal x(t)x(t) with fundamental period TT and fundamental frequency ω0=2π/T\omega_0 = 2\pi/T can be written as a weighted sum of harmonically related complex exponentials. This is the exponential Fourier series.

Synthesis equation

The set ϕk(t)=ejkω0t\phi_k(t) = e^{jk\omega_0 t}, k=0,±1,±2,…k = 0, \pm1, \pm2, \dots, contains signals that are all periodic with period TT (the kkth one has frequency kω0k\omega_0). A linear combination of them is also periodic with period TT:

x(t)=∑k=−∞∞ak ejkω0t=∑k=−∞∞ak ejk(2π/T)tx(t) = \sum_{k=-\infty}^{\infty} a_k\, e^{jk\omega_0 t} = \sum_{k=-\infty}^{\infty} a_k\, e^{jk(2\pi/T)t}

This is the synthesis equation. a0a_0 is the dc term, k=±1k = \pm1 are the fundamental components, and k=±Nk = \pm N are the NNth harmonics.

Analysis equation

To find aka_k, multiply both sides by e−jnω0te^{-jn\omega_0 t} and integrate over one period TT:

∫0Tx(t)e−jnω0t dt=∑k=−∞∞ak∫0Tej(k−n)ω0t dt\int_0^T x(t)e^{-jn\omega_0 t}\,dt = \sum_{k=-\infty}^{\infty} a_k \int_0^T e^{j(k-n)\omega_0 t}\,dt

Evaluate the integral on the right (orthogonality):

∫0Tej(k−n)ω0tdt=∫0Tcos⁡((k−n)ω0t) dt+j∫0Tsin⁡((k−n)ω0t) dt\int_0^T e^{j(k-n)\omega_0 t}dt = \int_0^T \cos((k-n)\omega_0 t)\,dt + j\int_0^T \sin((k-n)\omega_0 t)\,dt
  • For k≠nk \ne n, both integrals cover a whole number (k−n)(k-n) of periods, so they are 0.
  • For k=nk = n, the integrand is 1 and the integral is TT.
∫0Tej(k−n)ω0tdt={T,k=n0,k≠n\int_0^T e^{j(k-n)\omega_0 t}dt = \begin{cases} T, & k = n \\ 0, & k \ne n \end{cases}

So only the k=nk = n term survives:

∫0Tx(t)e−jnω0tdt=anT⇒an=1T∫0Tx(t)e−jnω0tdt\int_0^T x(t)e^{-jn\omega_0 t}dt = a_n T \quad\Rightarrow\quad a_n = \frac{1}{T}\int_0^T x(t)e^{-jn\omega_0 t}dt

Since any interval of length TT gives the same result, the analysis equation is

ak=1T∫Tx(t) e−jkω0t dta_k = \frac{1}{T}\int_{T} x(t)\,e^{-jk\omega_0 t}\,dt

The Fourier series pair

x(t)⟷FSakx(t) \overset{FS}{\longleftrightarrow} a_k
EquationFormula
Synthesisx(t)=∑kakejkω0tx(t) = \sum_k a_k e^{jk\omega_0 t}
Analysisak=1T∫Tx(t)e−jkω0tdta_k = \frac{1}{T}\int_T x(t)e^{-jk\omega_0 t}dt
DC valuea0=1T∫Tx(t) dta_0 = \frac{1}{T}\int_T x(t)\,dt (average value)

Notes:

  • The aka_k are the Fourier series coefficients or spectral coefficients; they are complex in general, ak=∣ak∣ej∠aka_k = |a_k|e^{j\angle a_k}, giving the magnitude and phase spectra.
  • For real x(t)x(t), a−k=ak∗a_{-k} = a_k^*, so ∣ak∣|a_k| is even and ∠ak\angle a_k is odd in kk.

Example: x(t)=cos⁡ω0t=12ejω0t+12e−jω0tx(t) = \cos\omega_0 t = \frac{1}{2}e^{j\omega_0 t} + \frac{1}{2}e^{-j\omega_0 t} gives a1=a−1=1/2a_1 = a_{-1} = 1/2 and all other ak=0a_k = 0.

✓ Answer checked by Claude Opus 5.5 (high effort)

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