Reconstruction: Undersampling and Filtering

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

Covers the importance of sampling, signal reconstruction, and aliasing in digital representation.

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

Emphasizes the necessity of filtering signals before sampling to prevent undersampling effects.

Explains how to fit the transmitter spectrum within the channel's bandwidth constraints.

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

Explores signal filtering using low-pass filters to reduce noise and distortions in signals, showcasing frequency suppression and smoothing effects.

Explores ideal low-pass filtering of signals to reduce noise and distortions.

Explores signal reconstruction, sampling frequency, and the stroboscopic effect.

Discusses memory cache organization and signal filtering techniques using a moving average filter to recover desired signals.