Abstract
Delay constrained multicast routing (DCMR) aims to construct a minimum-cost tree with end-to-end delay constraints. This routing problem is becoming more and more important to multimedia applications which are delay-sensitive and require real time communications. We solve the DCMR problem by the transiently chaotic neural network (TCNN) of Chen and Aihara. Simulation results show that the TCNN is more capable of reaching global optima compared with the Hopfield neural network (HNN).
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Liu, W., Wang, L. (2007). Solving the Delay Constrained Multicast Routing Problem Using the Transiently Chaotic Neural Network. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_8
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DOI: https://doi.org/10.1007/978-3-540-72393-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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