Resource arbitration using Neural networks
نویسنده
چکیده
In this paper we present the functional design of a resource arbiter based on Neural Networks. The decision for the access of the shared resource is based on a multilevel hierarchical Neural Network. The arbitration is based on a winner-take-all scheme and the priority measures are distributed in the neural network’s adaptive weights. The system is designed to learn externally from its history and guarantees fair resource sharing. The overall design is characterized by fairness, speed and modularity.
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