Lectures related to Undersampling

Bandpass Sampling

Covers bandpass sampling for signals with limited frequency range, ensuring information preservation through proper sampling techniques.

Data Representations and Processing

Covers data representations, challenges of imbalanced data, and strategies for data normalization and cleaning.

Reconstruction: Sampling Theorem

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

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.

Data Representations and Processing in Machine Learning

Covers data representations and processing techniques essential for effective machine learning algorithms.

Homodyne Receivers: Design and Challenges

Explores homodyne receivers, covering DC offset, channel selection, and offset cancellation, along with challenges like even-order distortion and LO leakage.

Reconstruction: Undersampling and Filtering

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

Filtering before Sampling

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

Complex Envelope: Signal Processing

Delves into the computation of bandpass and analytic signals using complex envelopes.

Signal Sampling

Explores representing analog signals digitally through sampling and quantization, discussing sampling frequency, undersampling consequences, and the stroboscopic effect.

Sampling Signals: Stroboscopic Effect (Spectrum Folding)

Covers the consequences of undersampling signals and the stroboscopic effect.

FIR-based sampling rate conversion

Covers rational sampling rate change, interpolation, Lagrange approximation, and FIR-based conversion.

Sampling of Signals 6: Sampling a Pure Sinusoid

Explores the sampling of pure sinusoids, emphasizing the Nyquist theorem and its practical implications.

Sinusoidal Modulation: Basics

Explores signal classification, sinusoidal modulation, applications, and demodulation techniques in the frequency domain.

Statistics & Experimental Design

Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.

Transition to/from Continuous Time Signals and Passband Modulation

Explores the transition between continuous time signals and passband modulation techniques.

Sampling and Reconstruction: Gaussian Signal Quality Analysis

Explores Fourier analysis, sampling, and signal reconstruction quality assessment through practical experiments.

Sampling strategies

Explores research process, variable types, causality vs correlation, and sampling strategies.

Optical Filtering: Products and Building Blocks

Explores optical filtering products and building blocks for various applications.

Frequency Response and Filters: Signals & Systems I

Explores frequency response, ideal filters, and linear phase in signals & systems.