When to use fourier integral instead of fourier series expansion

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SUMMARY

Fourier integrals are essential for analyzing non-periodic signals, while Fourier series expansions are applicable exclusively to periodic functions. The discussion highlights that Fourier integrals are suitable for square integrable functions and can utilize the Dirac delta function for periodic functions such as sine and cosine. In contrast, Fourier series should be employed when dealing with periodic functions. Understanding these distinctions is critical for accurate signal processing.

PREREQUISITES
  • Understanding of Fourier series and Fourier integrals
  • Knowledge of square integrable functions
  • Familiarity with the Dirac delta function
  • Basic principles of signal processing
NEXT STEPS
  • Study the properties of square integrable functions in detail
  • Learn about the applications of the Dirac delta function in signal processing
  • Explore the mathematical derivation of Fourier integrals
  • Investigate practical examples of Fourier series in periodic signal analysis
USEFUL FOR

Signal processing engineers, mathematicians, and students studying Fourier analysis will benefit from this discussion, particularly those focusing on the distinctions between Fourier integrals and series in signal representation.

Naughty Boy
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Suppose, I have a non-periodic signal for which amplitude spectrum is to be obtained . For this why should Fourier integral be used instead of Fourier series expansion . I want to know when to use Fourier inerals and when to use Fourier series . Please let me know all the details .
 
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If memory serves Fourier integral applies to square integrable functions and, with the use of Dirac delta function, to periodic functions like sine and cosine. The Fourier series expansion applies to periodic functions.
 
You use Fourier series if the function is periodic, transforms if it's not.
 

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