Solving optimization problems in communications using neural networks
The development of communication engineering (Internet, satellites, mobiles) changes our daily life. The optimization problems in communications have motivated research in computational intelligence techniques these years. To improve neural network algorithms for the shortest path routing problem (S...
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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2009
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| Online Access: | https://hdl.handle.net/10356/18828 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The development of communication engineering (Internet, satellites, mobiles) changes our daily life. The optimization problems in communications have motivated research in computational intelligence techniques these years. To improve neural network algorithms for the shortest path routing problem (SPRP), we propose a solution approach using a noisy Hopfield neural network (NHNN) by adding decaying stochastic noise to the continuous Hopfield neural network (HNN). We also improve the energy function for the SPRP. Simulation results show that our approach offers further improvements on route optimality rate compared to other algorithm that employ the HNN. |
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