Sampling (signal processing)

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Page 2 of 3

Data Representations and Processing

Covers data representations, challenges of imbalanced data, and strategies for data normalization and cleaning.

Frequency Estimation (Theory)

Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.

Networked Control Systems: Protocol-induced Delays and Time-varying Sampling

Explores protocol-induced delays, time-varying sampling, wireless control networks, and system stability.

State Space Control: Discrete Systems

Explores the shift from continuous to discrete control systems, focusing on the challenges and benefits of digital implementation.

Quantum Computing Fundamentals

Covers quantum computing fundamentals, ADC architectures, oversampling advantages, noise shaping, glitch phenomena, and digital integrated circuit noise.

Sinusoidal aliasing

Explores sinusoidal aliasing, from periodic complex exponentials to aliasing of sinusoids.

Nyquist Rate and Sampling Theorem

Explains the Nyquist rate and Sampling Theorem for reconstructing band-limited signals through examples and sampling techniques.

Sampling Complex Exponentials

Covers the sampling of complex exponentials and the challenges of reconstruction in different scenarios.

Discrete Fourier Transform: Frequency Periodicity and Reconstruction

Explores frequency periodicity in the discrete Fourier transform for signal reconstruction.

Sampling and Reconstruction Theory

Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.