Optical Computing: All-Analog Photoelectronic Chip for Vision Tasks

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Explores the automated picking of reinforcement bars within Ground Penetrating Radar data using machine learning and signal processing techniques.

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Covers advanced topics in watermarking, including resisting scaling and rotations, self-referenced watermarking, and types of attacks.

Project-Based Learning in Communications and Robotics

Introduces a project-based course in communications and robotics, emphasizing practical projects and independent learning to prepare students for real-world challenges.

Second-Order Model Compression

Explores second-order model compression for massive deep neural networks, showcasing compression techniques and their impact on model accuracy.

Adaptive Signal Processing: Filtering & Neural Networks

Explores adaptive signal processing, gradient descent, and the LMS algorithm for efficient filtering and neural network training.

Radar Technologies: Applications and Challenges in Robotics

Discusses radar technologies, their applications in robotics, and challenges in mmWave imaging.

Introduction to Signals and Filters

Covers the conversion of analog signals to digital, data compression, and signal reconstruction, highlighting the significance of signal processing in communication systems.

Neural Signals and Signal Processing

Explores nuclear magnetic resonance, MRI principles, pulse sequences, image reconstruction, safety considerations, and volume normalization in brain imaging.

Data Compression: Sparse Signals and Data Recording

Explores data compression through signal sparsity, questioning the need for recording vast amounts of data.

Neural Signals and Signal Processing

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