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When two signals are convolved in the time domain, what frequency components will be present in the frequency domain? Is it similar to (frequency 1 + frequency 2) \text{(frequency 1 + frequency 2)} (frequency 1 + frequency 2) and (frequency 1 - frequency 2) \text{(frequency 1 - frequency 2)} (frequency 1 - frequency 2) ? No, it isn’t. That formula applies to the time-domain multiplication of two sinusoidal signals. According to the Discrete Convolution Theorem, convolution of two discrete signals in the time domain is equivalent to multiplication of their DFTs in the frequency domain: F{x[n] ∗ h[n]} = X[k] ⋅ H[k] where X[k] and H[k] are the DFTs of x[n] and h[n] , respectively. Thus, the convolution y[n] in the time domain can be computed by taking the inverse DFT of the product: y[n] = F -1 {X[k] ⋅ H[k]} In general, the frequency components present in X[k]⋅H[k] correspond to the frequencies where both X[k] and H[k] have significant values. Frequencies in X[k] that align with