Durham School of Architectural Engineering and Construction
Date of this Version
4-26-2022
Citation
Patent No .: US 11,314,210 B2
Abstract
A continuous - time recurrent neural network ( CTRNN ) is described that exploits the nonlinear dynamics of micro electro - mechanical system ( MEMS ) devices to model a neuron in accordance with a neuron rate model that is the basis for dynamic field theory . Each MEMS device in the CTRNN is configured to simulate a neuron population by exploiting the characteristics of bi - stability and hysteresis inherent in certain MEMS device structures . In an embodiment , the MEMS device is a microbeam or cantilevered microbeam device that is excited with an alternating current ( AC ) voltage at or near an electrical resonance frequency associated with the MEMS device . In another embodiment , the MEMS device is an arched microbeam device that is excited with a direct current voltage and exhibits snap through behavior due to the physical design of the structure . A CTRNN can be implemented using a number of MEMS devices that are interconnected , the connections associated with varying connection coefficients .
Included in
Architectural Engineering Commons, Construction Engineering Commons, Environmental Design Commons, Other Engineering Commons