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ARTIFICIAL NEURAL NETWORK WITH TRAINABLE ACTIVATION FUNCTIONS AND FRACTIONAL DERIVATIVE VALUES

机译:具有可训练的激活函数和分数阶导数值的人工神经网络

摘要

Systems, apparatuses and methods may provide for technology that adjusts a plurality of weights in a neural network model and adjusts a plurality of activation functions in the neural network model. The technology may also output the neural network model in response to one or more conditions being satisfied by the plurality of weights and the plurality of activation functions. In one example, two or more of the activation functions are different from one another and the activation functions are adjusted on a per neuron basis.
机译:系统,装置和方法可以提供用于调整神经网络模型中的多个权重并调整神经网络模型中的多个激活函数的技术。该技术还可以响应于多个权重和多个激活函数满足的一个或多个条件来输出神经网络模型。在一个示例中,两个或多个激活函数彼此不同,并且在每个神经元的基础上调整激活函数。

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