Why Is Time Compression Represented by x(2t) in Signal Processing?

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SUMMARY

The discussion focuses on the concept of time compression in signal processing, specifically the transformation represented by x(2t). Participants clarify that time compression occurs when the time variable is scaled by a factor greater than one, resulting in a compressed signal. The transformation x(2t) indicates that for any point on the original signal x(t), the corresponding point on the compressed signal appears at half the original time value. This understanding is essential for grasping the principles of time scaling and transformation in signals and systems.

PREREQUISITES
  • Understanding of basic signal processing concepts
  • Familiarity with time-domain signal transformations
  • Knowledge of independent and dependent variables in mathematical functions
  • Basic graphing skills for visualizing signal transformations
NEXT STEPS
  • Study the concept of time scaling in signal processing
  • Learn about the mathematical representation of time transformations
  • Explore the implications of time compression on signal frequency
  • Investigate the relationship between time reversal and time scaling
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Students and professionals in electrical engineering, particularly those studying signals and systems, as well as anyone interested in understanding the mathematical transformations of signals in time domain analysis.

physio
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I have just started a course on signals and systems and am finding the subject confusing.
This question pertains to the transformations of the independent variable which is time in this case. I don't know why it is transformation of the "independent variable" as the time axis is the same as it originally was. The time axis is not "transformed". For example in time reversal of a signal, the signal is simply flipped about the origin and the time axis is unaltered (i.e. 't' stays the same but doesn't become '-t') yet the book says it is a transformation of the independent variable. Am I missing something?

After a reasonable amount of thought can anyone intuitively explain why time compression has a>1 i.e for a signal x(t) why and how x(2t) is the time compressed signal?? I think I will be able to answer the first question if I know why x(2t) is the compressed version of x(t).
 
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physio said:
I have just started a course on signals and systems and am finding the subject confusing.
This question pertains to the transformations of the independent variable which is time in this case. I don't know why it is transformation of the "independent variable" as the time axis is the same as it originally was. The time axis is not "transformed". For example in time reversal of a signal, the signal is simply flipped about the origin and the time axis is unaltered (i.e. 't' stays the same but doesn't become '-t') yet the book says it is a transformation of the independent variable. Am I missing something?
Hi physio. Think of it in two steps.
Step 1. Just re-label your time axis as "-t" instead of "t" in the right hand direction. Essentially this is all that the transformation actually involves, however convention requires that the "t" axis to run the other way (so that's why we need step 2).

Step 2. Flip both the "t" axis and the graph together. This step doesn't really change the graph, it merely puts it into the form people expect to see.

After a reasonable amount of thought can anyone intuitively explain why time compression has a>1 i.e for a signal x(t) why and how x(2t) is the time compressed signal?? I think I will be able to answer the first question if I know why x(2t) is the compressed version of x(t).

The best way to see this is to pick any particular point on your graph, say [itex]x_1 = x(t_1)[/itex] and notice that this same x point on the transformed graph occurs at a transform "t" value of [itex]t^* = t_1/2[/itex], (as [itex]x_1 = x(2(t_1/2))[/itex].
 
Thanks a lot for your reply uart! I understood the time reversal operation with your explanation but I yet have problems understanding the time scaling operation. I understood that the transformed variable t*=t1/2 i.e the transformed time variable is a scaled version (in this case t1 /2) of the original time variable. Hence shouldn't the transformed graph should be x(t*)?? Do we have to consider the graphs together for calculating the new function i.e. x(2t) or x(t/2) i.e. with reference with the original signal? Thanks in advance..!
 

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