Convolution - Signals and Systems

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Convolution can be applied to both discrete-time (DT) and continuous-time (CT) signals, with the primary distinction being the mathematical operations used: summation for DT signals and integration for CT signals. The convolution integral for CT signals is expressed as y(t) = ∫_{-∞}^{∞}x(τ)h(t-τ)dτ, while for DT signals, it is represented as y[n] = ∑_{k=-∞}^{∞}x[k]h[n-k]. Despite the different forms, the underlying operation remains consistent between the two types of signals. The terminology reflects this difference, with convolution summation used for DT and convolution integral for CT. Understanding these concepts is crucial for analyzing signals and systems effectively.
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I will make this my discussion thread. I have many questions to ask which I will post here. Please keep checking. All help will be appreciated.

My first question is: For discrete signal, we use variable 'n' and for continuous signal, we use variable 't'. But is the convolution integral valid for both. E.g. the only difference would be 'n' and 't'. Tau and integral will be the same?
 
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Convolution for a CT signal is defined as
<br /> y(t) = \int_{-\infty}^{\infty}x(\tau)h(t-\tau)d\tau<br />
and for DT it is defined as
<br /> y[n] = \sum_{k=-\infty}^{\infty}x[k]h[n-k]<br />

Thus for DT signal we do not have integral but summation.

Just to distinguish for DT case we call it convolution summation and for CT case we call it integral. But the operation is same!

Bhupala!
 
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