Convolution - Signals and Systems

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SUMMARY

The discussion centers on the concept of convolution in signals and systems, specifically distinguishing between discrete-time (DT) and continuous-time (CT) signals. For CT signals, convolution 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]. The key takeaway is that despite the different mathematical representations—integral for CT and summation for DT—the underlying operation remains fundamentally the same.

PREREQUISITES
  • Understanding of discrete-time (DT) and continuous-time (CT) signals
  • Familiarity with convolution operations in signal processing
  • Knowledge of integral calculus and summation notation
  • Basic concepts of signals and systems theory
NEXT STEPS
  • Study the properties of convolution in signal processing
  • Learn about the applications of convolution in filtering techniques
  • Explore the differences between linear and non-linear systems
  • Investigate the Fast Fourier Transform (FFT) and its relation to convolution
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Students and professionals in electrical engineering, signal processing, and systems analysis who seek to deepen their understanding of convolution and its applications in both discrete and continuous domains.

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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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