Reconstruction of Nonlinear Systems Using Delay Lines and Feedforward Networks
dc.contributor.author | Elliott, David L. | en_US |
dc.contributor.department | ISR | en_US |
dc.date.accessioned | 2007-05-23T09:58:39Z | |
dc.date.available | 2007-05-23T09:58:39Z | |
dc.date.issued | 1995 | en_US |
dc.description.abstract | Nonlinear system theory ideas have led to a method for approximating the dynamics of a nonlinear system in a bounded region of its state space, by training a feedforward neural network which is then reconfigured in recursive mode to provide a stand-alone simulator of the system. The input layer of the neural network contains time-delayed samples of one or more system outputs and control inputs. Autonomous systems can be simulated in this way by providing impulse inputs. | en_US |
dc.format.extent | 119741 bytes | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | http://hdl.handle.net/1903/5612 | |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | ISR; TR 1995-17 | en_US |
dc.subject | neural systems | en_US |
dc.subject | filtering | en_US |
dc.subject | nonlinear systems | en_US |
dc.subject | Intelligent Signal Processing | en_US |
dc.subject | Communications Systems | en_US |
dc.title | Reconstruction of Nonlinear Systems Using Delay Lines and Feedforward Networks | en_US |
dc.type | Technical Report | en_US |
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