A novel WDM optical time division multiplexing network (OTDMN) with great capacity is discussed.
提出了一种大容量的WD M光时分复用网络的概念。
At the same time, large-scale training of neural network algorithm put forward a slow sub-division of the network enhancement.
同时针对大规模神经网络算法训练速度较慢的问题提出了划分子网络的改进方法。
A linear quadratic Gaussian (LQG) stochastic optimal control was developed for networked control systems with network-induced delays longer than a sampling period using a time-division control mode.
对于网络诱发延迟大于一个采样周期的网络化控制系统，该文研究了该系统的线性二次Gauss (LQG)随机最优控制问题，提出了一种新的分时控制模式。
A linear quadratic Gaussian (LQG) stochastic optimal control was developed for networked control systems with network-induced delays longer than a sampling period using a time-division control mode.
对于网络诱发延迟大于一个采样周期的网络化控制系统，该文研究了该系统的线性二次Gauss (LQG)随机最优控制问题，提出了一种新的分时控制模式。
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