Resistive random-access memory (RRAM) can be used for the hardware implementation of neural networks. RRAM crossbar array architectures have been proposed for implementing vector-matrix multiplication and machine learning algorithms. A printed circuit board (PCB) consisting of mixed signals circuit blocks such as digital-to-analog (DAC) and analog-to-digital (ADC) converters is needed for the demonstration of prototype RRAM crossbars. This project will provide students the opportunity to gain experience with board-level mixed-signal design, programming of microcontrollers and peripheral interfaces, and to learn about resistive-switching memory and high-level understanding of machine learning algorithms.
Semester: Spring 2022
Hours per week: 5
E-mail Prof. Sanchez Esqueda (email@example.com) with your resume for further information. Project is FURI eligible for fall FURI application deadline.