| 摘要 |
A pyramidal pRAM neural network is used in an access control scheme for an ATM node, or other switch handling bursty traffic. Specifically, the neural network is a configured in a teacher forcing mode, and is trained either off-line or on-line. Cells arriving at the node, which are found to violate agreed quality of service parameters, may be dropped, depending on the expected state of the switch buffers, based on expected traffic arrival rates, but the control is adaptive, which means that violating cells may be allowed to gain access to the node, if the state of the switch allows it. Control is open-loop, which means that the response can be quicker. |
