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

In summary: 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 x_1 = x(t_1) and notice that this same x point on the transformed graph occurs at a transform "t" value of t^* = t_1/2, (as x_1 = x(2(t_1/2)).
  • #1
physio
68
1
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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  • #2
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].
 
  • #3
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..!
 

1. What is "time reversal" of a basic signal?

"Time reversal" of a basic signal refers to the process of reversing the order of the signal's samples, essentially playing the signal backwards.

2. What is the purpose of time reversal in signal processing?

The purpose of time reversal is to analyze the time-domain characteristics of a signal, such as its symmetry and phase, and to potentially reveal hidden patterns or information within the signal.

3. How is time reversal different from time inversion?

While time reversal involves reversing the order of a signal's samples, time inversion involves changing the direction of time in the signal, essentially flipping it upside down. Time inversion does not change the order of the samples, but it does affect the phase and frequency characteristics of the signal.

4. Can time reversal be applied to any type of signal?

Yes, time reversal can be applied to any type of signal, including audio, video, and digital signals. However, the effectiveness and usefulness of time reversal may vary depending on the characteristics of the signal.

5. What are some practical applications of time reversal in signal processing?

One practical application of time reversal is in ultrasonic imaging, where it can be used to enhance the resolution and accuracy of images. Time reversal has also been used in communication systems to improve signal quality and in acoustics to focus sound waves in a specific direction.

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