The effect of delays on the performance of Layer Recurrent Network
Layer Recurrent Network (LRN) is a dynamic network that has a feedback loop as well as a delay for each layer of the network except for the last layer. The main objective for this research is to study the effect of delays on the performance of the LRN in identifying a nonlinear model. A numerical ex...
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| Main Authors: | , , |
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2018
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| Online Access: | http://dspace.uniten.edu.my/jspui/handle/123456789/8920 |
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| Summary: | Layer Recurrent Network (LRN) is a dynamic network that has a feedback loop as well as a delay for each layer of the network except for the last layer. The main objective for this research is to study the effect of delays on the performance of the LRN in identifying a nonlinear model. A numerical experiment of the nonlinear model is set up before a set of input and output data is collected. The collected data is then used to train the LRN. The numbers of delays at the feedback loop is manipulated and the effect of the network performance is observed where it shows that the network has the best performance when the number of delay is set to more than the default/original value (which is one). © 2010 IEEE. |
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