Browsing by Advisor "Thakur, Chetan Singh"
Now showing items 1-4 of 4
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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 ... -
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 ...