Resources Contact Us Home
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
System for targeted delivery of therapeutic agents
System for the secure management of digitally controlled locks, operating by means of crypto acoustic credentials
Label printer
Alleviation of laser-induced damage in optical materials by suppression of transient color centers formation and control of phonon population
Method for improving the performance of browser-based, formula-driven parametric objects
Sacrificial spacer approach for differential source/drain implantation spacers in transistors comprising a high-k metal gate electrode structure
Process for the production of an acylation catalyst
  Randomly Featured Patents
UDDI registry extension for rating UDDI artifacts
Distance measuring device and method for adjusting photodetection unit of distance measuring device
Pair of suspenders
Method of manufacturing a piezoelectric device
Constant power, part load control strategy for electronic engine controls
Electronic scale
Cache table management device for router and program recording medium thereof
Production of lysosomal enzymes in plants by transient expression
Tie-down strap frame connector