A structure and training algorithm for quasi-diagonal recurrent neural network (QDRNN) is presented.

提出一种准对角递归神经网络(QDRNN)结构及学习算法。

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This provides a new way to the fast training of complex valued recurrent neural network.

这为快速训练复值递归神经网络提供了一条新的途径。

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An adaptive gradient descent algorithm for training simplified internally recurrent networks (SIRN) is developed and a new method of reconciling nonlinear dynamic data based on SIRN is proposed.

研究了简化型内回归神经网络基于自适应梯度下降法的训练算法，并提出了一种基于简化型内回归神经网络的非线性动态数据校核新方法。

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