Lectures related to Oversampling

Quantum Computing Fundamentals

Covers quantum computing fundamentals, ADC architectures, oversampling advantages, noise shaping, glitch phenomena, and digital integrated circuit noise.

Smart Sensors for the IoT: ADCs Fundamentals

Explores ADCs fundamentals for IoT smart sensors, covering quantization, non-idealities, and topologies.

Quantum and nanocomputing

Explores digital design principles, ADC architectures, FPGA-based ADCs, figures of merit, and lower bounds in digital design.

Oversampled D-A: Interpolation and Distortion

Explores oversampled D-A conversion, interpolation methods, and in-band distortion compensation.

Data Representations and Processing

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

LTI Systems: Analysis and Properties

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

Data Representations and Processing in Machine Learning

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

Signals & Systems II: Z Transform Properties and Inversion

Explores Z transform properties, ROC, inversion, and signal support behavior.

Transition to/from Continuous Time Signals and Passband Modulation

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

X-ray Imaging: Techniques and Applications

Explores synchrotrons, x-ray lasers, lensless imaging, Nyquist frequency, aliasing, oversampling, and constraints in scattering data analysis.

Nyquist Rate and Sampling Theorem

Explains the Nyquist rate and Sampling Theorem for reconstructing band-limited signals through examples and sampling techniques.

Data Preprocessing: Handling Challenges

Delves into advanced data preprocessing techniques, covering categorical encoding, missing data handling, and unbalanced datasets, emphasizing performance metrics and classifier comparison.

Image Processing I: Ordered Dithering and Fourier Transform

Explores ordered dithering and Fourier transform in image processing.

Analog to Digital Conversion

Explores analog to digital conversion principles, CMOS technology, precision limitations, and integration of converters.

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Wireless Receivers: Time and Phase Offset Compensation

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

Model Assessment: Metrics and Selection

Explores model assessment metrics, selection techniques, bias-variance tradeoff, and handling skewed data distributions in machine learning.

Sampling strategies

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

The Sampling Theorem

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

Signal Sampling and Reconstruction

Covers signal sampling, reconstruction, aliasing, and examples of signal reconstruction using low-pass filters.