本文讨论了一种基于循环神经网络的传感器补偿新方法。
An approach to compensating sensor drift based on recurrent neural networks is discussed in the paper.
提出一种新的基于基本样条逼近的循环神经网络，该网络易于训练且收敛速度快。
A new recurrent neural network based on B-spline function approximation is presented. The network can be easily trained and its training converges more quickly.
对角循环神经网络是一类经过修正的全连接循环神经网络，在系统动态行为的俘获方面具有明显的优势。
Diagonal recurrent neural network (DRNN) is a modified model of the fully connected recurrent neural network with the advantage in capturing the dynamic behavior of a system.
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