Fourier transform for Discrete signal

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SUMMARY

The discussion centers on the Fourier transform of a discrete signal defined as f(n) = a^n * u(n), where u(n) is the unit step function and 0 ≤ a < 1. The Fourier transform for discrete signals is expressed as F(i) = sum(f(n) * e^(-j2πn/N)), evaluated from n=0 to infinity. Participants clarify that the sum converges to F(i) = sum(1/(1 - a * e^(-j2πn/N))) due to the properties of the infinite geometric series, with the common ratio being r = a * e^(-j2πn/N).

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  • Understanding of discrete signals and the unit step function
  • Familiarity with Fourier transforms and their mathematical definitions
  • Knowledge of geometric series and convergence criteria
  • Basic complex number manipulation and exponential functions
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  • Study the properties of the unit step function in signal processing
  • Learn about the convergence of infinite geometric series
  • Explore the application of Fourier transforms in analyzing discrete signals
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Students and professionals in signal processing, electrical engineering, and applied mathematics who are looking to deepen their understanding of Fourier transforms and discrete signal analysis.

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let us asuume this discrete signal:

f(n)=a^n * u(n) ; where u(n) is unit step function
; u(n)=1 where n>=0
u(n)=0 where n<0
;0=<a<1
and the foruier transform for discrete signals is defined as :
F(i)=sum ( f(n)*e^(-j2*pi*n/N) ;n=0 to inifinity

i know that the sum is equal to:

F(i)=sum(1/(1-a*e^-j2*pi*n/N)

but actually i don't know why! could anyone help!


thanks in advance!
 
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Hint: think infinite geometric series. In this example, what is the common ratio r?

Regards,
George
 
what do you mean by common ratio r?
 

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