Browsing by Advisor "Thakur, Chetan Singh"
Now showing items 1-7 of 7
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Analog Compute for Edge-AI: Devices, Circuits & SoC
Machine Learning and Artificial Intelligence research has yielded models with huge computational complexities to solve a multitude of problems. These complex models require substantial computational resources to perform ... -
Energy-efficient Hardware and Algorithmic Techniques for Design of Low-power Intelligent Systems
Low-power design techniques involving hardware and algorithms framework are a fundamental challenge of the modern electronic system. The internet connects devices (IoTs) with advanced capabilities in sensing and processing ... -
Event-Related Potential Interpretation Approaches for Neonatal Hearing Screening
Biopotentials are the electrical discharges generated from the human body. They reflect the status underlying the phenomenon and are frequently used to assess the real-time physiological status of the human body. ... -
Low Power Analog Neural Network Framework with MIFGMOS
Ever since the beginning of the notion behind the term 'cloud computing,' i.e., to share the pro- cessing and storage capabilities of a centralized system, there has been a signi cant increase in the availability of raw ... -
Low Power Machine Learning Systems for Energy Efficient Edge Devices
Energy-efficient devices are essential in the world of edge computing and the tiny Machine Learning (tinyML) paradigm. Edge devices are often constrained by the available compu- tational power and hardware resource. To ... -
Neuromorphic Silicon Retinas: Analog and Digital Models
Silicon retinas are artificial retinal devices designed to replicate the functionality of the biological retina using silicon-based technologies. These retinas aim to address visual impairment by capturing and processing ... -
Neuromorphic Vision: Asynchronous and Sparse Processing of Event Camera Data
Modern systems, including edge computing, autonomous vehicles and robotics, face constraints, such as limited processing power and restricted battery energy, making computational efficiency a critical bottleneck for their ...