Abstract
We present a method to compute the delay constrained multicast routing tree by employing chaotic neural networks. Experimental result shows that the noisy chaotic neural network (NCNN) provides optimal solution more often compared to the transiently chaotic neural network (TCNN) and the Hopfield neural network (HNN). Furthermore, compared with the bounded shortest multicast algorithm (BSMA), the noisy chaotic neural network is able to find multicast trees with lower cost.
| Original language | English |
|---|---|
| Pages (from-to) | 82-89 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Computers |
| Volume | 58 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2009 |
| Externally published | Yes |
Keywords
- Chaos
- Constrained Steiner tree (CST)
- Multicast routing
- Neural networks
- Noise
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