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System Identification Using a Hybrid Feed Forward Neural Networks | ||
| journal of al-qadisiyah for pure science(quarterly) | ||
| Article 1, Volume 7, Issue 4, 2007, Pages 221-229 PDF (0 K) | ||
| Abstract | ||
| A back-propagation feed forward neural network with three layers was applied for different systems identifications. The intermediate layer (hidden layer) of the proposed neural network is built with hybrid activation functions provided with two different activation functions namely linear activation function and hyperbolic tangent activation function. The results show the ability of the network to identify linear as well as nonlinear system with high speed of convergence comparing with traditional neural network structures. Without the need to build networks that have activation factions correspond the applied system. | ||
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