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
Case for camera
Carbon dioxide capture system and methods of capturing carbon dioxide
Physiological measuring system comprising a garment in the form of a sleeve or glove and sensing apparatus incorporated in the garment
Method, system and computer program product for managing funds in custodial deposit accounts
Managing multiple web services on a single device
System and method for testing an integrated circuit embedded in a system on a chip
Event-associating software application for accessing digital media
  Randomly Featured Patents
Rodent-resistant non-conductive optical fiber cable
Polyester multifilament yarn and a process for manufacturing the same
Spherical toy
Novel cyclopropane carboxylic acid esters
Display device with rail support
Composite substrate for use in magnetic recording-and-reproducing device
Image-dependent color shifting of strongly color shifted images
Three-way solenoid valve
Renally active tetrapeptides
Editing of customised documents