Explores physics-informed imaging systems, including lensless imaging, deep learning for imaging challenges, and the development of noise models for low-light videos.
Explores electrical metrology, covering random variables, noise sources, and their impact on electronic devices.
Explores different types of noise in devices and circuits, including interference noise, inherent noise, and random signals.
Introduces the basics of supervised learning, focusing on logistic regression, linear classification, and likelihood maximization.
Explores electronic, thermomechanical, and amplifier noise, calibration of amplitude, frequency tracking, and system limits.
Explores different types of noise in electrical systems and their impact on electronic devices.
Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.
