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| Titel: |
Retrieval of surface parameters using dynamic learning neural network |
| Auteur: |
Chen, K. S. Kao, W. L. Tzeng, Y. C. |
| Verschenen in: |
International journal of remote sensing |
| Paginering: | Jaargang 16 (1995) nr. 5 pagina's 801-809 |
| Jaar: |
1995-03-20 |
| Inhoud: |
A highly dynamic learning (DL) neural network is developed and applied to perform the inversion of rough surface parameters: dielectric constant, surface rms height, and correlation length, The network training scheme is based on the Kalman filter technique which lends itself to a highly dynamic and adaptive merit during the learning stage. The training data sets utilized were obtained from the Integral Equation Model (IEM) which has a wide range of frequency. The training speed of the network is found to be much faster than the back-propagation (BP) trained multi-layer preceptron (MLP) with the same degree of accuracy. When applied to invert the surface parameters, the DL network shows a very satisfactory result in terms of learning time and process accuracy which thus enhances its potential applications to remote sensing of rough surfaces. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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