Fourier transform and steady state solution?

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SUMMARY

The discussion centers on the relationship between Fourier transforms and steady state solutions in signal processing. It establishes that the Fourier transform can effectively identify the frequency components of both stationary signals, such as f(t) = cos(20πt) + cos(50πt) + cos(100πt) + cos(200πt), and transient signals, like g(t), despite their differing characteristics. The Fourier transform reveals that both signals exhibit similar frequency components, specifically 10 Hz, 25 Hz, 50 Hz, and 100 Hz. For analyzing transient signals, the discussion suggests utilizing alternative methods such as wavelet transforms.

PREREQUISITES
  • Understanding of Fourier transforms and their applications in signal processing.
  • Knowledge of stationary and transient signals.
  • Familiarity with the mathematical representation of signals.
  • Basic concepts of wavelet transforms for transient signal analysis.
NEXT STEPS
  • Study the mathematical properties of Fourier transforms in detail.
  • Learn about the differences between stationary and transient signals.
  • Explore wavelet transforms and their advantages over Fourier transforms for transient signals.
  • Investigate practical applications of Fourier analysis in real-world signal processing scenarios.
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Students, engineers, and researchers in signal processing, particularly those interested in the analysis of stationary and transient signals using Fourier and wavelet transforms.

hanson
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Hi all!
I am asking about a question about Fourier transform.
I can only roughly remember things about Fourier transform.
I am told that Fourier transform gives the steady state solution, is it?
I can hardly relate these two concepts.
Can someone try to explain?
Many thanks.
 
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May be http://users.rowan.edu/~polikar/WAVELETS/WTpart1.html" might give a clue in understanding.

Let say that we have a signal
f(t) = cos(20\pi t) + cos(50\pi t) + cos(100\pi t) + cos(200\pi t)
which is a stationary signal (steady state I presume). The Fourier transform of this signal will identify that this signal has frequencies of 10, 25, 50, and 100 Hz at any given time instant.
Next consider another signal of period 1s,

g(t)=\left\{\begin{array}{cc}cos(200\pi t),&amp;\mbox{ if }<br /> 0\leq t &lt; 0.3 \\<br /> cos(100\pi t), &amp; \mbox{ if } 0.3 \leq t &lt; 0.6 \\<br /> cos(50\pi t), &amp; \mbox{ if } 0.6 \leq t &lt; 0.8 \\<br /> cos(20\pi t), &amp; \mbox{ if } 0.8 \leq t &lt; 1 <br /> \end{array}\right

Signal g(t) is a transient signal. But the Fourier transforms of g(t) and f(t) are almost identical. So given some coeffients, the Fourier transform will identify the signal as f(t) the stationary signal.
To analyse the second signal we use other transform e.g. wavelet transform.

What am I writing here?
 
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