该神经网络模型结构简单，便于硬件实现。
The architecture of this neural network is relatively simple, and easily implemented by the hardware.
控制系统的硬件采用了DSP芯片，以保证系统的实时性；软件采用了模糊-神经网络算法，以克服系统模型的不确定性。
DSP chip is applied in hardware design to ensure real-time performance of control system, and fuzzy-neural network algorithm is adopted to overcome uncertainness of control model.
提出了一种用于修正光学神经网络硬件系统误差的虚拟神经网络模型。
The optical experimental results show that the virtual network can efficiently correct the errors of hardware system.
提出了一种用于修正光学神经网络硬件系统误差的虚拟神经网络模型。
A virtual neural network model for correcting the errors of hardware system is proposed.
提出了一种用于修正光学神经网络硬件系统误差的虚拟神经网络模型。
A virtual neural network model for correcting the errors of hardware system is proposed.
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