Patent ID: 7398259
Filing Date: 2008-07-08
Classification: G06N,Y10S

Abstract:
1. A physical neural network system based on nanotechnology, comprising: an electromechanical-based physical neural network having at least one synaptic component, wherein said at least one synaptic component of said electromechanical-based physical neural network comprises a dielectric medium with a plurality of nanoconductors disposed in said dielectric medium; a mechanism for modifying a strength of said at least one synaptic component, whereby said plurality of nanoconductors suspended in said dielectric medium and free to move about are subject to a dielectrophoretic force resulting from an exposure to a time-varying electric field, wherein said dielectrophoretic force includes a dipole-induced force that is utilized to attract or repel said plurality of nanoconductors to an electrode gap formed between at least one pre-synaptic electrode and at least one post-synaptic electrode that form said at least one synaptic component of said electromechanical-based physical neural network; and a feedback circuit for training said electromechanical-based physical neural network by providing a feedback signal to said physical neural network for modifying said at least one synaptic component of said electromechanical-based physical neural network to accomplish a particular neural network task based on a neural network training rule, thereby permitting said electromechanical-based physical neural network to provide for a physical process capable of self-assembly and self-repair and wherein said electromechanical-based physical neural network functions as a physical mechanism that emulates said neural network training rule.