Short notes

Continuous Time Fourier Transform Short Notes

A single rectangular pulse of width τ = 1 ms and amplitude A through an ideal channel is the standard CTFT example that every signals textbook opens with — its transform is Aτ·sinc(fτ), a sinc function centred at DC with first null at 1/τ = 1 kHz. That sinc shape in the frequency domain is what tells a communication engineer the minimum bandwidth needed to pass the pulse without distortion, making CTFT the core tool of spectral analysis.

EEE, ECE, EI

How it works

The CTFT pair is X(jω) = ∫x(t)e^(−jωt)dt and x(t) = (1/2π)∫X(jω)e^(jωt)dω. Key transform pairs to memorise: δ(t) ↔ 1 (flat spectrum), u(t) ↔ πδ(ω) + 1/jω, e^(−at)u(t) ↔ 1/(a+jω) for a > 0, and rect(t/τ) ↔ τ·sinc(ωτ/2). The convolution property states that convolution in time maps to multiplication in frequency: x(t)*h(t) ↔ X(jω)H(jω). This is why filter design works — an ideal low-pass filter with cutoff ω_c has a rectangular H(jω), meaning its impulse response h(t) is a sinc function, non-causal and therefore physically unrealisable.

Key points to remember

The CTFT exists for signals satisfying the Dirichlet conditions or that are square-integrable. Time-shifting property: x(t−t₀) ↔ e^(−jωt₀)X(jω) — only phase changes, magnitude is unaffected. Frequency shifting (modulation): x(t)e^(jω₀t) ↔ X(j(ω−ω₀)). Differentiation in time: dx/dt ↔ jω·X(jω), explaining why differentiators amplify high-frequency noise. Parseval's theorem: ∫|x(t)|² dt = (1/2π)∫|X(jω)|² dω links time-domain energy to frequency-domain energy. The duality property — if x(t) ↔ X(jω), then X(jt) ↔ 2πx(−ω) — is a favourite trick question.

Exam tip

The examiner always asks you to find the CTFT of e^(−at)u(t) and then apply the time-shifting or frequency-shifting property to a modified version — show every step of the integration to claim full marks even if the final answer is a standard pair.

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