Digital Communication Systems - Autocorrelation

Click For Summary
SUMMARY

The discussion focuses on determining the autocorrelation of the output signal X(t) from a linear system, where X(t) is defined as X(t) = W(t) - W(t - 1) and W(t) is a white noise process with a power spectral density of unity (N_0/2 = 1). Participants express confusion regarding the transition between different autocorrelation functions and the application of Dirac delta functions in the solution. The key takeaway is that the autocorrelation function of a white noise process is represented by a Dirac delta function, which simplifies the analysis of the system's output.

PREREQUISITES
  • Understanding of autocorrelation functions in signal processing
  • Familiarity with linear systems and their properties
  • Knowledge of white noise processes and their spectral characteristics
  • Basic proficiency in mathematical transformations involving Dirac delta functions
NEXT STEPS
  • Study the properties of autocorrelation functions in detail
  • Explore linear system response to white noise inputs
  • Learn about the application of Dirac delta functions in signal processing
  • Investigate the implications of power spectral density in communication systems
USEFUL FOR

Students and professionals in electrical engineering, particularly those focusing on signal processing, communication systems, and linear system analysis.

GreenPrint
Messages
1,186
Reaction score
0

Homework Statement



A white noise process W(t) with unity (N_0/2 = 1) power spectral density is input to a linear system. The output of the linear system is X(t), where

X(t) = W(t) - W(t - 1)

Determine the autocorrelation of X(t) and sketch it.

Homework Equations



Capture.png

Let τ denote a time shift; that is, t = t_2 and τ = t_1 - t_2
Capture.png


The Attempt at a Solution



Capture.png

I understand that the first term on the last line is indeed equal to
Capture.png
. I'm however unsure what to do with the other three terms. The solution sets the other three terms to different autocorrelation functions and I'm not sure how these other three terms are autocorrelation functions as well based off of the definition.

Here's what the solution is. I don't understand how it went from the second line to the third line.
Capture.png

Any help would be greatly appreciated. I also don't understand how how the solution goes from the third line to the fourth line. It seems to just simply replacing the autocorrelation functions with dirac delta functions. I'm not sure how these are equal in any way.
 
Physics news on Phys.org
sorry I didn't mean to post
 

Similar threads

  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 4 ·
Replies
4
Views
4K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K