A Study of the Charge Trap Transistor (CTT) for Post-Fab Modification of Wafers

Abstract

This report summarizes a year-long study on the applicability of the charge trap transistor (CTT) for embedded memory applications. Two case uses are considered (1) as a digital multi-time programmable memory and (2) as are programmable analog memory. Experimental data reveals that a CTT for analog memory applications possesses promising characteristics for implementing synapses in neural networks, such as spike-timing dependent plasticity, very fine tunability, weight-dependent plasticity, and low power consumption. Ongoing efforts include the design and tape out of a CTT-based neuromorphic chip for digit recognition, and more elaborate designs that address programming time, scalability, power/area reduction, redundancy, unsupervised learning, etc. in the long-term.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2018
Accession Number
AD1050743

Entities

People

  • Subramanian Iyer

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Air Force Research Laboratories
  • Artificial Neural Networks
  • Complementary Metal-Oxide Semiconductors
  • Computer Programming
  • Dielectrics
  • Energy Consumption
  • Experimental Data
  • Field Effect Transistors
  • Governments
  • Logic Gates
  • Materials
  • Memory Devices
  • Metal Oxide Semiconductors
  • Metal Oxides
  • Recognition
  • Reliability
  • Semiconductors
  • Standards
  • Unsupervised Machine Learning

Readers

  • Integrated Circuit Design and Technology.
  • Neuroscience
  • Parallel and Distributed Computing.

Technology Areas

  • AI & ML