| 摘要 |
A method of speeding up the execution of a wide class of neural networks for processing input signals evolving slowly through time, such as, for instance, voice, radar, sonar, video signals, and which requires no specialized, costly or hard-to-find hardware. The method requires storing, for the neurons in at least one level of the network, the activation value at a certain instant and comparing it with the one computed at the subsequent instant. If the activation is equal, the neuron carries out no activity, otherwise it propagates the difference in activation, multiplied by the interconnection weights, to the neurons it is connected to.
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