Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

Sampling strategies

Description

This lecture explains the importance of sampling strategies for signals, focusing on band-limited signals and the potential issues of aliasing. It covers the concept of raw sampling, band-limiting signals, ideal low-pass filtering, sync sampling, and sync interpolation, emphasizing the need to control errors in the sampling process. The lecture also discusses the projection onto the space of band-limited functions, mean square error minimization, and the reconstruction of continuous time signals from samples.

Official source

Related concepts (32)

Band-stop filter

In signal processing, a band-stop filter or band-rejection filter is a filter that passes most frequencies unaltered, but attenuates those in a specific range to very low levels. It is the opposite of a band-pass filter. A notch filter is a band-stop filter with a narrow stopband (high Q factor). Narrow notch filters (optical) are used in Raman spectroscopy, live sound reproduction (public address systems, or PA systems) and in instrument amplifiers (especially amplifiers or preamplifiers for acoustic instruments such as acoustic guitar, mandolin, bass instrument amplifier, etc.

Low-pass filter

A low-pass filter is a filter that passes signals with a frequency lower than a selected cutoff frequency and attenuates signals with frequencies higher than the cutoff frequency. The exact frequency response of the filter depends on the filter design. The filter is sometimes called a high-cut filter, or treble-cut filter in audio applications. A low-pass filter is the complement of a high-pass filter. In optics, high-pass and low-pass may have different meanings, depending on whether referring to the frequency or wavelength of light, since these variables are inversely related.

Filter (signal processing)

In signal processing, a filter is a device or process that removes some unwanted components or features from a signal. Filtering is a class of signal processing, the defining feature of filters being the complete or partial suppression of some aspect of the signal. Most often, this means removing some frequencies or frequency bands. However, filters do not exclusively act in the frequency domain; especially in the field of many other targets for filtering exist.

Anti-aliasing filter

An anti-aliasing filter (AAF) is a filter used before a signal sampler to restrict the bandwidth of a signal to satisfy the Nyquist–Shannon sampling theorem over the band of interest. Since the theorem states that unambiguous reconstruction of the signal from its samples is possible when the power of frequencies above the Nyquist frequency is zero, a brick wall filter is an idealized but impractical AAF. A practical AAF makes a trade off between reduced bandwidth and increased aliasing.

High-pass filter

A high-pass filter (HPF) is an electronic filter that passes signals with a frequency higher than a certain cutoff frequency and attenuates signals with frequencies lower than the cutoff frequency. The amount of attenuation for each frequency depends on the filter design. A high-pass filter is usually modeled as a linear time-invariant system. It is sometimes called a low-cut filter or bass-cut filter in the context of audio engineering. High-pass filters have many uses, such as blocking DC from circuitry sensitive to non-zero average voltages or radio frequency devices.

Related lectures (56)

Signal Filtering MOOC: Information, Computation, Communication: Introduction to computational thinking

Explores signal filtering using low-pass filters to reduce noise and distortions in signals, showcasing frequency suppression and smoothing effects.

Memory Cache Organization and Signal Filtering

Discusses memory cache organization and signal filtering techniques using a moving average filter to recover desired signals.

Digital Filtering: Butterworth Filter Design

Explores digital Butterworth filter design, covering scaling, stable poles, and filter application.

Fitting the Transmitter Spectrum

Explains how to fit the transmitter spectrum within the channel's bandwidth constraints.

Reconstruction: Undersampling and Filtering