Oversampling refers to:

Oversampling refers to:

• A. Sampling at a rate lower than Nyquist
• B. Sampling at a rate greater than Nyquist
• C. Sampling at exactly Nyquist
• D. Not sampling at all

Answer: (B)

Oversampling means sampling faster than the minimum rate needed to capture all the information in a signal. The minimum rate is the Nyquist rate, which is twice the highest frequency present in the signal. Sampling above that rate provides a guard band in the frequency domain, making accurate reconstruction easier and allowing anti-aliasing filters to be less steep. It also spreads quantization noise over a wider bandwidth, which can improve effective resolution after appropriate processing. So, sampling at a rate greater than Nyquist is oversampling. Sampling below the Nyquist rate leads to aliasing, where different frequency components become indistinguishable and distort the signal. Sampling exactly at Nyquist is theoretically possible but impractical in real systems due to non-ideal filters and edge effects. Not sampling at all obviously fails to capture any signal.

Oversampling means sampling faster than the minimum rate needed to capture all the information in a signal. The minimum rate is the Nyquist rate, which is twice the highest frequency present in the signal. Sampling above that rate provides a guard band in the frequency domain, making accurate reconstruction easier and allowing anti-aliasing filters to be less steep. It also spreads quantization noise over a wider bandwidth, which can improve effective resolution after appropriate processing. So, sampling at a rate greater than Nyquist is oversampling.

Sampling below the Nyquist rate leads to aliasing, where different frequency components become indistinguishable and distort the signal. Sampling exactly at Nyquist is theoretically possible but impractical in real systems due to non-ideal filters and edge effects. Not sampling at all obviously fails to capture any signal.