Resources Contact Us Home
Browse by: INVENTOR PATENT HOLDER PATENT NUMBER DATE
 
 
Recurrent neural networks teaching system










Image Number 7 for United States Patent #5182794.

A teaching method for a recurrent neural network having hidden, output and input neurons calculates weighting errors over a limited number of propagations of the network. This process permits the use of conventional teaching sets, such as are used with feedforward networks, to be used with recurrent networks. The teaching outputs are substituted for the computed activations of the output neurons in the forward propagation and error correction stages. Back propagated error from the last propagation is assumed to be zero for the hidden neurons. A method of reducing drift of the network with respect to a modeled process is also described and a forced cycling method to eliminate the time lag between network input and output.








 
 
  Recently Added Patents
Universal data-driven computer proxy
Automated user interface adjustment
Categorization of design rule errors
Method and device for managing devices in device management system
Protective vest
Closed-loop adaptive adjustment of pacing therapy based on cardiogenic impedance signals detected by an implantable medical device
Method and device for accessing the documentation of an aircraft according to alarms generated therein
  Randomly Featured Patents
Transverse flux electrical machine with segmented core stator
Method of reforming a tip portion of a probe
Automobile tire
Method for fabricating anisotropic conductive substrate
Method for treating cellulosic material
Integrated circuit testing
Removable penetration fittings using T-fitting and flexible pipe combination
Search method and circuit
Method for automated isolation of fractions in multichannel separation systems
Communications network