Lectures related to Signal Reconstruction: Sampling Theorem and Interpolation Formula

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

Covers parameter estimation in wireless receivers and phase ambiguity in signal modeling.

Covers Lagrange interpolation using intervals to find accurate polynomial approximations.

Covers the principles of digital communication, focusing on the Nyquist Sampling Theorem and signal space dimension.

Covers the basics of Newton interpolation and interpolation polynomials using Lagrange and Newton methods.

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

Covers the Newton method for finding zeros of functions using data interpolation.

Explores the relationships between various transforms and signal embedding techniques.