Statement (I): Aliasing occurs when the sampling frequency is less tha...
Explanation: Aliasing is an irreversible process. Once aliasing has occurred then signal can-not be recovered back.
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Statement (I): Aliasing occurs when the sampling frequency is less tha...
Statement (I): Aliasing occurs when the sampling frequency is less than twice the maximum frequency in the signal.
Aliasing is a phenomenon that occurs in signal processing when the sampling rate is insufficient to accurately represent the original continuous signal.
When a continuous signal is sampled, the sampling theorem states that in order to avoid aliasing, the sampling frequency should be at least twice the maximum frequency component in the signal. This is known as the Nyquist-Shannon sampling theorem.
Therefore, Statement (I) is true. Aliasing does occur when the sampling frequency is less than twice the maximum frequency in the signal.
Statement (II): Aliasing is a reversible process.
Aliasing is not a reversible process. Once aliasing occurs, the information about the original signal is lost and cannot be recovered.
When aliasing occurs, high-frequency components of the signal fold back into the frequency range of interest, resulting in distortion and the inability to accurately reconstruct the original signal. This is particularly evident in digital audio and image processing.
Therefore, Statement (II) is false. Aliasing is not a reversible process.
Explanation:
The correct answer is option (c) Statement (I) is true but Statement (II) is false.
Aliasing is a critical issue in signal processing and can lead to incorrect interpretation of the sampled data. It is important to ensure that the sampling frequency is sufficiently high to avoid aliasing and accurately represent the original signal. If the sampling frequency is too low, high-frequency components of the signal will be improperly represented, leading to distorted and misleading results.
To mitigate aliasing, an anti-aliasing filter is often employed before the sampling process. This filter removes high-frequency components from the signal that are above the Nyquist frequency, preventing them from folding back into the frequency range of interest.
In conclusion, aliasing occurs when the sampling frequency is insufficient, and it is not a reversible process. It is crucial to understand and address the issue of aliasing in signal processing applications to ensure accurate and reliable results.
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