How Does a Linear System Respond to a Sine Wave Input Using Fourier Transform?

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SUMMARY

The discussion focuses on analyzing the response of a linear system described by the differential equation y' + y = x, where the input x is a sine wave function, x = sin(t). The Fourier Transform is utilized to derive the system's response, represented by the relationship Y(jω) = H(jω)X(jω), where H(jω) is the system's transfer function. The convolution theorem is applied to express the output y(t) as the convolution of the system's impulse response h(t) and the input x(t). Additionally, the Fourier Transform of the derivative y'(t) is addressed, emphasizing the need to understand its implications in the context of linear systems.

PREREQUISITES
  • Understanding of linear differential equations, specifically y' + y = x.
  • Familiarity with Fourier Transform concepts and notation.
  • Knowledge of convolution and its application in signal processing.
  • Basic understanding of transfer functions in linear systems.
NEXT STEPS
  • Study the properties of the Fourier Transform, particularly in relation to derivatives.
  • Explore the concept of impulse response and its significance in system analysis.
  • Learn about the convolution theorem and its applications in signal processing.
  • Investigate the implications of transfer functions in control systems design.
USEFUL FOR

Students and professionals in engineering, particularly those specializing in signal processing, control systems, and applied mathematics. This discussion is beneficial for anyone looking to deepen their understanding of linear system responses to sinusoidal inputs using Fourier analysis.

jaguar515
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Find the response of the of the linear system at rest
y' + y = x , where x = sin(t)
using the Fourier transform and formulas :

Y(jw)=H(jw)X(jw)
y(t)=h(t)*x(t) convolution
 
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jaguar515 said:
Find the response of the of the linear system at rest
y' + y = x , where x = sin(t)
using the Fourier transform and formulas :

Y(jw)=H(jw)X(jw)
y(t)=h(t)*x(t) convolution
If the FT of y(t) is [tex]Y(j\omega)[/tex] what is the FT of y'(t)?
 

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