DURIP FABRICATION OF BRAIN-INSPIRED NETWORKS FOR MULITIFUNCTIONAL INTELLIGENT SYSTEMS

Abstract

This Defense University Instrumentation Program (DURIP) proposal aims to establish key instruments and perform researches to fabricate brain-inspired networks for multifunctional intelligent systems. This project will facilitate an AFOSR Multidisciplinary University Research Initiative (MURI), entitled Brain-Inspired Networks for Multifunctional Intelligent Systems in Aerial Vehicles (PI- Yong Chen, UCLA, Award Number- FA9550-19-1-0213). In this proposal, we plan to perform research on (A) an advanced sputtering machine for the preparations of novel composite materials to fabricate devices including synaptic resistors (synstors), memory resistors (memristors), and neuristors to emulate the signal processing and learning functions of synapses, and the nonlinear dynamic functions of neurons; (B) an ultrafast pico-ampere electric testing system to study synstors, memristors, and neuristors in order to understand the fundamental mechanisms of the devices, and develop the advanced functions of the devices to emulate synapses and neurons; (C) large scale self- programming neuromorphic integrated circuits (SNIC) that operates in analog parallel mode, facilitates processing and real-time learning, is more than six orders of magnitude more efficient than the supercomputer, and consumes a power of ~1 mW; (D) interface printed circuit boards to integrate multiple SNICs with distributed networks of sensors and actuators to demonstrate multifunctional intelligent systems with structural health-monitoring, automatic navigation, and real-time learning in self-piloted unmanned aerial vehicles.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 07, 2023
Source ID
FA95502110350

Entities

People

  • Yong Chen

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of California, Los Angeles

Tags

Readers

  • Electrical Engineering
  • Neural Network Machine Learning.
  • Research Science/Academic Research

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control