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How can aliasing error be avoided? - Answers

Aliasing error can be avoided by using appropriate sampling techniques, such as the Nyquist theorem, which states that a signal should be sampled at least twice its highest frequency to accurately reconstruct it. Implementing anti-aliasing filters before sampling can also help by removing high-frequency components that could cause distortion. Additionally, increasing the sampling rate can reduce the risk of aliasing by capturing more detail in the signal.



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How can aliasing error be avoided? - Answers

https://math.answers.com/math-and-arithmetic/How_can_aliasing_error_be_avoided

Aliasing error can be avoided by using appropriate sampling techniques, such as the Nyquist theorem, which states that a signal should be sampled at least twice its highest frequency to accurately reconstruct it. Implementing anti-aliasing filters before sampling can also help by removing high-frequency components that could cause distortion. Additionally, increasing the sampling rate can reduce the risk of aliasing by capturing more detail in the signal.



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https://math.answers.com/math-and-arithmetic/How_can_aliasing_error_be_avoided

How can aliasing error be avoided? - Answers

Aliasing error can be avoided by using appropriate sampling techniques, such as the Nyquist theorem, which states that a signal should be sampled at least twice its highest frequency to accurately reconstruct it. Implementing anti-aliasing filters before sampling can also help by removing high-frequency components that could cause distortion. Additionally, increasing the sampling rate can reduce the risk of aliasing by capturing more detail in the signal.

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      Aliasing error can be avoided by using appropriate sampling techniques, such as the Nyquist theorem, which states that a signal should be sampled at least twice its highest frequency to accurately reconstruct it. Implementing anti-aliasing filters before sampling can also help by removing high-frequency components that could cause distortion. Additionally, increasing the sampling rate can reduce the risk of aliasing by capturing more detail in the signal.

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