Title :
Single-electron latching switches as nanoscale synapses
Author :
Fölling, Simon ; Turel, Özgur ; Likharev, Konstantin
Author_Institution :
State Univ. of New York, Stony Brook, NY, USA
Abstract :
Nanoscale latching switches based on controllable single-electron transfer and trapping may serve as a synaptic basis for extremely dense and fast self-evolving BiWAS (binary weight, analog signal) neural networks. We have designed and simulated two devices of this type, a “propagating” switch and a “branching” switch, as well as multi-entry switching nodes based on their combination. We have also carried out a preliminary study of two architectures of neural networks based on 2D arrays of the switching nodes: a “free-growing” network in which the shape of axonic and dendritic trees may be very complex, and a “randomized distributed crossbar” network in which axons and dendrites are implemented as straight wire segments. The latter network scales much better, but the former one may be more adequate for input parts of very large scale networks
Keywords :
Monte Carlo methods; nanotechnology; neural chips; 2D arrays; axonic trees; binary weight analog signal neural networks; branching switch; controllable single-electron transfer; controllable single-electron trapping; dendritic trees; free-growing network; multi-entry switching nodes; nanoscale synapses; propagating switch; randomized distributed crossbar network; self-evolving BiWAS neural networks; single-electron latching switches; synaptic basis; very large scale networks; Bismuth; CMOS technology; Electron traps; Nerve fibers; Neural networks; Shape; Single electron devices; Switches; Voltage; Wires;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939020