Lectures related to Filtering before Sampling

Sampling: Signal Reconstruction and Aliasing

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.

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

Covers the concepts of sampling and reconstruction in signal processing, explaining the conditions for accurate reconstruction.

A/D and D/A Conversion Fundamentals

Covers the fundamentals of A/D and D/A conversion techniques and their implementation.

Signals, Instruments, and Systems

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

Signal Sampling 4: Ideal Low-Pass Filtering

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

Filtering and Sampling of Signals

Explores filtering signals with a moving average filter and the process of sampling, emphasizing the importance of signal reconstruction from samples.

Reconstruction: Undersampling and Filtering

Explores the impact of undersampling on signals and the solution of pre-filtering to avoid the stroboscopic effect.

Numerical Control of Dynamic Systems

Covers topics like digital filtering, stability, and discrete systems, including experiments and manipulations.

Linear Time Invariant Filters: Time Series

Explores estimation, ergodicity, sampling, and linear time invariant filters in time series analysis.

Sampling: DT-time processing of CT signals

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

Signal Filtering

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

Frequency Response of LTI Systems

Explores LTI systems, impulse response, convolution, system properties, and frequency response, including low-pass and band-pass filters.

Signals & Systems I: Sampling and Reconstruction

Explores ideal sampling, Fourier transformation, spectral repetition, and analog signal reconstruction.

Reconstruction: Sampling Theorem

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

Sampling Signals: Stroboscopic Effect (Spectrum Folding)

Covers the consequences of undersampling signals and the stroboscopic effect.

Wireless Receivers: Time and Phase Offset

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

Electrical Metrology: Noise Reduction Techniques

Explores noise reduction techniques in electrical metrology, covering properties of charge, current, voltage, noise sources, and filtering methods.

Reconstruction: Sampling Theorem Conclusion

Explores the fundamental concept of reconstructing signals through sampling, emphasizing the importance of applying a low-pass filter before sampling.