Shrivastava Awarded Patent for Developing Self-powered Machine Learning Vision Architecture for Edge IoT application

Aatmesh Shrivastava

ECE Assistant Professor Aatmesh Shrivastava was awarded a patent for “Self-powered analog computing architecture with energy monitoring to enable machine-learning vision at the edge.”

Abstract Source: USPTO

An analog computing method includes the steps of: (a) generating a biasing current (IWi) using a constant gm bias circuit operating in the subthreshold region for ultra-low power consumption, wherein gm is generated by PMOS or NMOS transistors, the circuit including a switched capacitor resistor; and (b) multiplying the biasing current by an input voltage using a differential amplifier multiplication circuit to generate an analog voltage output (VOi). In one or more embodiments, the method is used in a vision application, where the biasing current represents a weight in a convolution filter and the input voltage represents a pixel voltage of an acquired image.

Related Faculty: Aatmesh Shrivastava

Related Departments:Electrical & Computer Engineering