Process for forming synapses in neural networks and resistor therefor
Patent
·
OSTI ID:870526
- San Francisco, CA
Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA
- DOE Contract Number:
- W-7405-ENG-48
- Assignee:
- Regents of University of California (Oakland, CA)
- Patent Number(s):
- US 5538915
- OSTI ID:
- 870526
- Country of Publication:
- United States
- Language:
- English
Resistive synaptic interconnects for electronic neural networks
|
journal | July 1987 |
An introduction to computing with neural nets
|
journal | January 1987 |
A laser direct write double-level-metal technology for rapid fabrication
|
conference | January 1990 |
Similar Records
Process for forming synapses in neural networks and resistor therefor
Laser programmable integrated curcuit for forming synapses in neural networks
Laser programmable integrated circuit for forming synapses in neural networks
Patent
·
Tue Jul 23 00:00:00 EDT 1996
·
OSTI ID:264572
Laser programmable integrated curcuit for forming synapses in neural networks
Patent
·
Tue Dec 31 23:00:00 EST 1996
·
OSTI ID:870831
Laser programmable integrated circuit for forming synapses in neural networks
Patent
·
Mon Feb 10 23:00:00 EST 1997
·
OSTI ID:441872
Related Subjects
/438/
amorphous
amorphous silicon
array
conductor
conductors
connected
create
customizable
customizable neural
desired
doped
energy
extremely
form
forming
forming synapses
highly
highly doped
identical
issues
laser
laser energy
laser wavelength
layer
material
metal
metal conduct
metal conductor
metal conductors
network
networks
neural
neural net
neural network
neural networks
occupying
process
processing
processing issues
reflectivity
resistances
resistor
resistor material
resistors
resistors form
series
severable
silicon
simplifying
spaces
synapse
synapses
synaptic
synaptic array
typical
uppermost
uppermost layer
wavelength
amorphous
amorphous silicon
array
conductor
conductors
connected
create
customizable
customizable neural
desired
doped
energy
extremely
form
forming
forming synapses
highly
highly doped
identical
issues
laser
laser energy
laser wavelength
layer
material
metal
metal conduct
metal conductor
metal conductors
network
networks
neural
neural net
neural network
neural networks
occupying
process
processing
processing issues
reflectivity
resistances
resistor
resistor material
resistors
resistors form
series
severable
silicon
simplifying
spaces
synapse
synapses
synaptic
synaptic array
typical
uppermost
uppermost layer
wavelength