Identifying time and/or amplitude transformations

In summary, the conversation is about identifying the time and/or amplitude transformations needed to obtain a specific signal from a given signal x(t). The transformations should follow a specific order, with time shifting before time scaling and amplitude scaling before amplitude shifting. The question is asking for the transformations to be chosen in a way that follows this order. The person is having trouble understanding the question and is seeking clarification on what parts of the equation represent time shifting and amplitude scaling.
  • #1
Drew Carter
5
0
So the question looks like this:
Identify the time and/or amplitude transformations that must be applied to the signal x(t) in order to obtain each
of the signal specified below. Choose the transformations such that time shifting precedes time scaling and
amplitude scaling precedes amplitude shifting. Be sure to clearly indicate the order in which the transformations
are to be applied.
(e) y(t) = −3x(2[t −1])−1

I've tried everything. I can't figure this out
 
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  • #2
Try to break it down. Which parts of your equation represent a time shift and which are an amplitude scaling?
 
  • #3
olivermsun said:
Try to break it down. Which parts of your equation represent a time shift and which are an amplitude scaling?
I guess I know the parts that are time shift and amplitude scaling. I just don't get what the question is asking. Do i write the parts and label them? I slightly get the first part of the question. It's the "chose the transformation such that" part that's confusing me. I don't need answers or anything. I just can't figure out the question.
 

Related to Identifying time and/or amplitude transformations

What is time transformation and why is it important?

Time transformation refers to the process of altering a signal or data set in terms of time. This is important in scientific research as it allows for the analysis and comparison of data at different time scales, which can provide valuable insights into various processes and phenomena.

What are some common methods for identifying time transformations?

Some common methods for identifying time transformations include Fourier analysis, wavelet analysis, and autocorrelation. These techniques allow researchers to identify patterns and trends in data at different time scales and can help to reveal underlying relationships and dynamics.

How does amplitude transformation affect data analysis?

Amplitude transformation refers to the scaling or changing of the magnitude of a signal or data set. This can have a significant impact on data analysis, as it can alter the perceived relationships and patterns within the data. It is important to carefully consider and account for any amplitude transformations in order to accurately interpret data.

What are some potential applications of time and amplitude transformations?

Time and amplitude transformations have a wide range of applications in various scientific fields, including astronomy, geology, and biomedical research. They can be used to analyze and compare data from different time periods or to study complex systems with multiple variables.

What are some challenges in identifying and interpreting time and amplitude transformations?

One challenge in identifying time and amplitude transformations is the potential for data artifacts or noise to obscure the true patterns and dynamics. Additionally, it can be challenging to determine the appropriate time or amplitude scale to use for analysis, as this may vary depending on the specific research question and data set.

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