Update Functions

Two new update functions have been implemented for partial recurrent networks:

• JE_Order:
  This update function propagates a pattern from the input layer to the first hidden layer, then to the second hidden layer, etc. and finally to the output layer. After this follows a synchronous update of all context units.

• JE_Special:
  This update function can be used for iterated long-term predictions. If the actual prediction value is part of the next input pattern to predict the next value , the input pattern can not be generated before the needed prediction value is available. For long-term predictions many input patterns have to be generated in this manner. To generate these patterns manually means a lot of effort.

  Using the update function JE_Special these input patterns will be generated dynamically. Let n be the number of input units and m the number of output units of the network. JE_Special generates the new input vector with the output of the last n-m input units and the outputs of the m output units. The usage of this update function requires n > m. The propagation of the new generated pattern is done like using JE_Update. The number of the actual pattern in the remote panel has no meaning for the input pattern when using JE_Special.