System identification using neural networks and higher order statistics
The objective of this dissertation is to use neural network technology, in conjunction with second order statistics and higher order statistics, to identify signal models. Classical system identification method has always been based on the assumption that the observed signal is Gaussian. This type o...
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| Format: | Thesis |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/10356/19677 |
| Summary: | The objective of this dissertation is to use neural network technology, in conjunction with second order statistics and higher order statistics, to identify signal models. Classical system identification method has always been based on the assumption that the observed signal is Gaussian. This type of system can be identified using the first and second order statistics, i.e mean and covariance sequence. |
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