Lectures related to Quantization (signal processing)

Neural Signal Compression

Explores analog-to-digital conversion, neural signal optimization, multichannel architectures, and on-chip compression techniques in neuroengineering.

Smart Sensors for the IoT: ADCs Fundamentals

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

Quantization: Basics and Uniform Input

Explores quantization in digital devices, covering scalar and uniform quantization, mean square error, and signal-to-noise ratio.

Neural Signals and Signal Processing

Explores neural signals, EMG control, muscle synergies, and HD-EMG for prosthetic devices.

Neural Signals and Signal Processing

Covers neural signals, brain enthusiasm, neuroimaging, and statistical analysis in neuroimaging studies.

Transistor Bipolar Modeling: Application Examples

Explores small signal models of bipolar transistors with application examples and discusses gain in voltage, Early effect, and temperature behavior.

Image Processing I: Quantization and Histogram Analysis

Explores image quantization, histogram analysis, and the trade-off between spatial and grayscale resolution.

Neural Signals and Signal Processing

Explores neural signal processing for brain-computer interfaces, including decoding techniques like Kalman filters and spike sorting.

Quantization and Coding of Digital Signals

Explores quantization and coding of digital signals, discussing uniform quantization, error analysis, and signal-to-quantization noise ratio.

Fundamental Notions - I

Explores fundamental notions in image and video processing, covering applications and key concepts like color quantization and 2D Fourier Transform properties.

Quantization and Coding: Uniform Quantization

Explains uniform quantization in signal processing and how quantization noise increases with each additional bit.

Neural Signals and Signal Processing

Delves into neural signals, GLM, ANOVA, brain mapping, connectivity, and multivariate methods.

Hardware Technologies and Applications

Explores hardware technologies, quantum electronics, cryogenic systems, quantum computing, and ADC architectures.

Neural Signals and Signal Processing: Methods and Designs

Explores neural signal processing methods, fMRI designs, GLM analysis, and quality control.

Neural Signals and Signal Processing

Explores neural signals, EMG processing, muscle synergies, and prosthetic control using advanced signal processing techniques.

Quantum Signal Processing

Covers IQ demodulation of noisy quantum signals using FPGA and MATLAB.

Model Compression: Techniques for Efficient NLP Models

Explores model compression techniques in NLP, discussing pruning, quantization, weight factorization, knowledge distillation, and attention mechanisms.

Quantization: Topological Operators

Covers the quantization of topological operators and Ising models on square lattices.

Signal Processing: Sampling and Reconstruction

Covers the concepts of quantization, coding, and sampling in signal processing.

Neural Signals and Signal Processing: Hemodynamic Imaging

Explores hemodynamic imaging techniques to measure brain activity and understand brain structure and function.