Lectures related to Sinc filter

The ideal lowpass filter

Explores the ideal lowpass filter, its impulse and frequency response, and challenges due to infinite support and lack of stability.

Oversampled D-A: Interpolation and Distortion

Explores oversampled D-A conversion, interpolation methods, and in-band distortion compensation.

The spectrum of interpolated signals

Explores sinc interpolation and the spectral representation of interpolated signals based on the chosen interpolation period.

Raw sampling: FS-Band-Limited functions

Discusses raw sampling of FS-Band-Limited functions and its limitations.

Signal Sampling: Interpolation

Explores signal sampling theory, interpolation techniques, and the importance of the sampling theorem in signal processing.

Sampling strategies

Explores sampling strategies for signals, emphasizing the importance of controlling errors in the sampling process.

Impulse Truncation: Gibbs Phenomenon

Explores impulse truncation to approximate ideal filters, leading to the Gibbs Phenomenon.

Practical Sampling and Interpolation

Covers practical sampling, interpolation challenges, spectral representation, and Fourier Transform properties.

Reconstruction Theorem: Sampling Theorem Elements

Explores the reconstruction theorem and the sampling conditions for accurate signal reconstruction based on the sampling frequency and signal bandwidth.

JSON Representation with Case Classes

Covers the representation of JSON data using case classes in Scala.

Ideal filters derived from the ideal lowpass filter

Covers the derivation of ideal high pass and band pass filters.

Frequency Sampling

Explores the frequency sampling method to approximate ideal filters, useful for quick prototyping but lacking fine control over errors.

Signal Reconstruction: Basics MOOC: Information, Computation, Communication: Introduction to computational thinking

Explores signal reconstruction basics, including interpolation techniques and formulas using triangular and sinc functions.

FIR-based sampling rate conversion

Covers rational sampling rate change, interpolation, Lagrange approximation, and FIR-based conversion.

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.

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Fast Fourier Transform (FFT): Lecture 4

Covers the Fast Fourier Transform (FFT) algorithm, interpolation, filters, image processing, and experimental techniques in TEM and STM.

Filtering and Sampling of Signals

Explores filtering signals with a moving average filter and the process of sampling, emphasizing the importance of signal reconstruction from samples.

Upsampling: Basics

Explores the basics of upsampling in signal processing, including continuous time, digital domain, and frequency domain techniques.

LTI Systems: Analysis and Properties Log in to Mediaspace to watch this video

Covers the analysis and properties of Linear Time-Invariant (LTI) systems.