Decomposition of apriodic and periodic signals

In summary, the decomposition of periodic signals results in discrete frequencies due to the use of the signal's period as a key tool, while the decomposition of aperiodic signals results in continuous frequencies due to the infinitely long period of such signals.
  • #1
Geek007
10
0
Hi there,
why the decomposition of periodic Composite signal give discrete frequencies and decomposition of aperiodic signal give continuous(in decimal) frequencies. please kindly do explain the concept behind in as simple words possible.
Thanks
 
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  • #2
One hand wavy argument makes use the period of the signal as the key tool. Let's say there is a periodic signal with period ##T##, then in the frequency domain, adjacent frequency components are separated by ##M\pi/T## where ##M## is an integer. As for a nonperiodic signal, we can view it as a periodic signal with infinitely long period, ##T \to \infty##. Therefore, the separation between adjacent frequency components will be ##\lim_{T\to \infty} M\pi/T = 0##, yielding a continuous spectrum.
 

Related to Decomposition of apriodic and periodic signals

1. What is the difference between aperiodic and periodic signals?

Aperiodic signals are signals that do not repeat themselves and have no defined period or frequency. They can be random or non-repetitive in nature. On the other hand, periodic signals have a specific repeating pattern and can be represented by a single frequency and period.

2. How do you decompose aperiodic and periodic signals?

Aperiodic signals can be decomposed using techniques such as Fourier transform, wavelet transform, and time-frequency analysis. These techniques break down the signal into its individual frequency components. Periodic signals can be decomposed using Fourier series, which represent the signal as a sum of sinusoidal functions.

3. Why is it important to decompose signals?

Decomposing signals allows us to analyze and understand the different components of a signal. It can help us identify patterns, trends, and anomalies in the signal. This is especially useful in fields such as signal processing, communication, and data analysis.

4. Can a signal be both aperiodic and periodic?

No, a signal cannot be both aperiodic and periodic. A signal is either aperiodic or periodic based on its repeating pattern. If a signal has a repeating pattern, it is considered periodic. If it does not have a repeating pattern, it is considered aperiodic.

5. Are there any real-life examples of aperiodic and periodic signals?

Aperiodic signals can be found in natural phenomena such as earthquake signals, heart rate variability, and weather patterns. Periodic signals can be found in electrical signals, musical notes, and mechanical vibrations.

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