Wireless Sensor Network Modeling Using Modified Recurrent Neural Network: Application to Fault Detection

Wireless Sensor Network Modeling Using Modified Recurrent Neural Network: Application to Fault Detection

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Wireless Sensor Networks (WSNs) consist of a large number of sensors, which in turn have their own dynamics. They interact with each other and the base station, which controls the network. In multi-hop wireless sensor networks, information hops from one node to another and finally to the network gateway or base station. Dynamic Recurrent Neural Networks (RNNs) consist of a set of dynamic nodes that provide internal feedback to their own inputs. They can be used to simulate and model dynamic systems such as a network of sensors.APPENDIX B SIMULATION SOURCE CODE USING MATLAB 7.1 103 APPENDIX B BIBLIOGRAPHY 112.


Title:Wireless Sensor Network Modeling Using Modified Recurrent Neural Network: Application to Fault Detection
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Publisher:ProQuest - 2008
ISBN-13:

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