Sampling and Reconstruction of Signals topics include: A/D Converters and their oversampling, band pass signal sampling and representation, sample and hold concepts and quantization and coding techniques. Sampling and reconstruction are processes that convert continuous-time signals into a sequence of numbers and back again. Sampling converts continuous-time signals, like sound, into a sequence of numbers that can be stored, manipulated, and transmitted by computers. Reconstruction converts the samples back into a continuous-time format for physical presentation. For example,... Show more Sampling and Reconstruction of Signals topics include: A/D Converters and their oversampling, band pass signal sampling and representation, sample and hold concepts and quantization and coding techniques. Sampling and reconstruction are processes that convert continuous-time signals into a sequence of numbers and back again. Sampling converts continuous-time signals, like sound, into a sequence of numbers that can be stored, manipulated, and transmitted by computers. Reconstruction converts the samples back into a continuous-time format for physical presentation. For example, reconstruction can create sound. The Nyquist-Shannon sampling theorem, also known as the sampling theorem or the Nyquist criterion, states that a signal can be perfectly reconstructed from its samples if the sampling rate is at least twice the highest frequency in the signal. The sampling theorem prevents "aliasing," which is when high-frequency content appears as lower frequencies, distorting the signal during reconstruction. Related concepts: Quantization: The process of sampling an analog signal and converting those samples to digital values, or symbols, that can be used to recreate a close approximation of the original analog signal. Aliasing: A phenomenon that is directly related to sampling. It is caused by an incorrectly reconstructed signal, due to insufficient sampling. Basis-based reconstruction theory: According to this theory, the discrete signal is reconstructed into a continuous signal. Show less
Sampling and Reconstruction of Signals topics include: A/D Converters and their oversampling, band pass signal sampling and representation, sample and hold concepts and quantization and coding techniques.
Sampling and reconstruction are processes that convert continuous-time signals into a sequence of numbers and back again.
Sampling converts continuous-time signals, like sound, into a sequence of numbers that can be stored, manipulated, and transmitted by computers. Reconstruction converts the samples back into a continuous-time format for physical presentation. For example, reconstruction can create sound.
The Nyquist-Shannon sampling theorem, also known as the sampling theorem or the Nyquist criterion, states that a signal can be perfectly reconstructed from its samples if the sampling rate is at least twice the highest frequency in the signal. The sampling theorem prevents "aliasing," which is when high-frequency content appears as lower frequencies, distorting the signal during reconstruction.
Related concepts:
Quantization: The process of sampling an analog signal and converting those samples to digital values, or symbols, that can be used to recreate a close approximation of the original analog signal. Aliasing: A phenomenon that is directly related to sampling. It is caused by an incorrectly reconstructed signal, due to insufficient sampling. Basis-based reconstruction theory: According to this theory, the discrete signal is reconstructed into a continuous signal.
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