Comparisons of Seven Neural Network Models on Traffic Control Problems in Multistage Interconnection Networks
Issue No. 04 - April (1993 vol. 42)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/12.214695
<p>The performances of seven neural network models for traffic control problems in multistage interconnection networks are compared. The decay term, three neuron models, and two heuristics were evaluated. The goal of the traffic control problems is to find conflict-free switching configurations with the maximum throughput. The simulation results show that the hysteresis McCullock-Pitts neuron model without the decay term and with two heuristics has the best performance.</p>
neural network models; traffic control problems; multistage interconnection networks; decay term; neuron models; heuristics; conflict-free switching configurations; simulation results; hysteresis McCullock-Pitts neuron model; multiprocessor interconnection networks; neural nets; parallel algorithms.
N. Funabiki, Y. Takefuji, K.C Lee, "Comparisons of Seven Neural Network Models on Traffic Control Problems in Multistage Interconnection Networks", IEEE Transactions on Computers, vol. 42, no. , pp. 497-501, April 1993, doi:10.1109/12.214695