Which term describes the process of sampling a signal at intervals and assigning a numeric value?

Which term describes the process of sampling a signal at intervals and assigning a numeric value?

• A. sampling rate
• B. linear filtering
• C. sampling skew
• D. aliasing

Answer: (A)

The term that describes the process of sampling a signal at intervals and assigning a numeric value is known as the sampling rate. The sampling rate defines how often the signal is sampled over a specific period, and it is crucial for accurately reconstructing the original signal from its samples. In digital signal processing, the higher the sampling rate, the more accurately the digital representation will capture the nuances of the analog signal. Sampling involves taking measurements at specific points in time and converting these measurements into numeric values that can be processed by digital systems. This quantization of the analog signal allows it to be stored, manipulated, and transmitted as digital data, which is essential in applications like audio processing, medical imaging, and telecommunications. Other terms, such as linear filtering, sampling skew, and aliasing, relate to different concepts within signal processing. Linear filtering involves manipulating the signal in the frequency domain to enhance or attenuate certain features. Sampling skew refers to the timing discrepancies that can occur in a system, affecting data integrity. Aliasing occurs when a signal is undersampled, resulting in different signals becoming indistinguishable, emphasizing the importance of a proper sampling rate.

The term that describes the process of sampling a signal at intervals and assigning a numeric value is known as the sampling rate. The sampling rate defines how often the signal is sampled over a specific period, and it is crucial for accurately reconstructing the original signal from its samples. In digital signal processing, the higher the sampling rate, the more accurately the digital representation will capture the nuances of the analog signal.

Sampling involves taking measurements at specific points in time and converting these measurements into numeric values that can be processed by digital systems. This quantization of the analog signal allows it to be stored, manipulated, and transmitted as digital data, which is essential in applications like audio processing, medical imaging, and telecommunications.

Other terms, such as linear filtering, sampling skew, and aliasing, relate to different concepts within signal processing. Linear filtering involves manipulating the signal in the frequency domain to enhance or attenuate certain features. Sampling skew refers to the timing discrepancies that can occur in a system, affecting data integrity. Aliasing occurs when a signal is undersampled, resulting in different signals becoming indistinguishable, emphasizing the importance of a proper sampling rate.