SamplingBandbreite

SamplingBandbreite is the range of frequencies that a sampling system can faithfully capture or reconstruct from an analog signal. In practice, it is determined by the sampling rate and the anti-aliasing filtration that precedes the sampler. The maximum unambiguous input frequency is the Nyquist frequency, equal to half the sampling rate (fs/2). Content above this limit will fold back (alias) into lower frequencies unless it is removed by a pre-sampling filter. Therefore, the effective SamplingBandbreite is typically the Nyquist bandwidth, B = fs/2, and the input signal should be band-limited to this range before sampling.

If the input contains frequencies beyond the Nyquist limit, the sampled data will contain aliased components that distort the reconstructed signal. To avoid this, a pre-sampling anti-aliasing filter with a cutoff below fs/2 is used; in practice, designers account for transition bands and real-world filter imperfections that affect performance. Other non-idealities, such as quantization noise, jitter in the sampling clock, and hardware limitations, also influence the realized bandwidth and signal quality.

In applications, SamplingBandbreite informs ADC design, digital signal processing, and communications. For example, a 44.1 kHz audio system has a nominal SamplingBandbreite of about 22 kHz, suitable for human hearing, while higher sampling rates (e.g., 96 kHz) extend the potential bandwidth. The concept is fundamental to the sampling theorem and to understanding how spectral replicas arise in the discrete-time domain.