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    • 8. 发明授权
    • Temporally dynamic artificial neural networks
    • 时间动态人工神经网络
    • US08630966B2
    • 2014-01-14
    • US12657748
    • 2010-01-27
    • Fred H. GageJames Bradley AimoneJanet Wiles
    • Fred H. GageJames Bradley AimoneJanet Wiles
    • G06N3/08
    • G06N3/082
    • An apparatus, article and method containing an artificial neural network that, after training, produces new trainable nodes such that input data representative of a first event and input data representative of a second event both activate a subset of the new trainable nodes. The artificial neural network can generate an output that is influenced by the input data of both events. In various embodiments, the new trainable nodes are sequentially produced and show decreasing trainability over time such that, at a particular point in time, newer produced nodes are more trainable than earlier produced nodes. The artificial neural network can be included in various embodiments of methods, apparatus and articles for use in predicting or profiling events.
    • 一种包含人造神经网络的装置,物品和方法,其在训练之后产生新的可训练节点,使得表示第一事件的输入数据和表示第二事件的输入数据都激活新的可训练节点的子集。 人造神经网络可以产生受两个事件的输入数据影响的输出。 在各种实施例中,新的可训练节点被顺序地产生并且随着时间的推移显示降低的可训练性,使得在特定的时间点,较新的生成的节点比先前产生的节点更可训练。 人造神经网络可以包括在用于预测或分析事件的方法,装置和物品的各种实施例中。