Canonical Representation of Discrete Signals

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

Covers the generation of signals with noise, sampling, and conversion to digital.

Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.

Explores the link between DTFT, Z-transforms, and Fourier transforms, vector analogy, and discrete signals.

Covers Analog-Digital and Digital-Analog conversion, including sampling, quantization, Flash converter, weighted current generation, and R2R network.

Explores analog and digital signal processing, A/D and D/A conversion, resolution, settling time, and digital interfaces in electronic circuits.

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

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

Introduces the discrete Fourier transform, a key tool for digital signal analysis.