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A neural network approach to the traffic control problem in reverse baseline networks (1993)

Sun, K. T. ; Fu, H. C.

Springer

Circuits, systems and signal processing 12 (1993), S. 247-261

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ISSN: 1531-5878

Source: Springer Online Journal Archives 1860-2000

Topics: Electrical Engineering, Measurement and Control Technology

Notes: Abstract A neural network for the traffic control problem applied to reverse baseline networks has been proposed in this paper. This problem has been first represented by an energy function. A neural network is applied for maximizing the energy of the function under the constraints of the reverse baseline network. The number of iteration steps in our neural network is limited by a performed upper bound O(n), wheren is the size of ann ×n network. The throughputs of our neural network have been shown by the empirical results to be better than the conventional algorithm (modified Bipartite Matching Algorithm) when the packet densities rise higher than 50%.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1007/BF01189876

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