Signal Processing: Sampling and Reconstruction

Related lectures (32)

Page 1 of 4

Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.

Covers the importance of sampling in signal processing, including the sampling theorem and signal reconstruction.

Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.

Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.

Covers the basics of the Fourier transform and its applications in signal processing.

Covers sampling, Fourier Transform, and reconstruction using low-pass filters in signal processing.

Covers the basics of signal processing, including Fourier transform, linear systems, and signal manipulation.

Emphasizes the significance of vector spaces in signal processing, offering a unified framework for various signal types and system design.

Covers the basics of signal processing and electric circuits.

Covers the impact and compensation of time and phase offset in wireless receivers.