Are g(t) = f(t) + f(-t) and g(t) = f(t/2) time variant and non-causal filters?

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In summary, causality in science refers to the relationship between cause and effect, and is used to explain and predict phenomena. Time variance describes changes in a system over time and is closely related to causality in science. Both causality and time variance can be measured in scientific research, and examples of these phenomena include weather patterns, economic fluctuations, and the spread of diseases.
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skan
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1.g(t) = f(t) + f(-t)
2. g(t)= f(t/2)
can someone pls explain why these functions are time variant and non causal
 
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  • #2
This sounds like it's from a DSP course. Is it ? Are you talking about filters ?
 
  • #3
yeah I am ! they are filters.
 

1. What is causality in science?

Causality is the relationship between cause and effect, where one event (the cause) leads to another event (the effect). In science, causality is used to explain and predict phenomena in the natural world.

2. What does it mean for something to be time variant?

Time variance refers to changes or fluctuations in a system over time. In science, it is often used to describe how a particular phenomenon or variable may change in relation to time.

3. How are causality and time variance related?

Causality and time variance are closely related in science. Time variance can affect the relationship between cause and effect, and can also be used to study the causal mechanisms behind a particular phenomenon.

4. Can causality and time variance be measured?

Yes, both causality and time variance can be measured in scientific research. Causality can be measured through experiments and statistical analyses, while time variance can be measured through various methods such as time series analysis and trend analysis.

5. What are some examples of causal and time variant phenomena?

Examples of causal and time variant phenomena include weather patterns, economic fluctuations, and the spread of diseases. In each of these examples, there are causal relationships between different variables, and these relationships can change over time.

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