A small 4-channel time-delayed complex perceptron is used as a silicon photonic neural network (PNN) device to compensate for chromatic dispersion in optical fiber links. The PNN device is experimentally tested with non-return-to-zero optical signals at 10 Gbps after propagation through up to 125 km optical fiber link. During the learning phase, a separation-loss function is optimized in order to maximally separate the transmitted levels of 0s from the 1s, which implies an optimization of the bit-error-rate. Testing of the PNN device shows that the excess losses introduced by the PNN device are compensated by the gain in the transmitted signal equalization for a link longer than 100 km. The measured data are reproduced by a model that accounts for the optical link and the PNN device. This allows simulating the network performances for higher data rates, where the device shows improvement with respect to the benchmark both in terms of performance and ease of use.

中文翻译：

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通过小型硅光子延时神经网络均衡 10 Gbps IMDD 信号

小型 4 通道延时复数感知器用作硅光子神经网络 (PNN) 设备，以补偿光纤链路中的色散。PNN 设备在通过长达 125 公里的光纤链路传播后，使用 10 Gbps 的不归零光信号进行了实验测试。在学习阶段，分离损失函数被优化，以最大程度地分离 0 和 1 的传输级别，这意味着误码率的优化。PNN 设备的测试表明，对于长度超过 100 公里的链路，由 PNN 设备引入的额外损耗可以通过传输信号均衡中的增益进行补偿。测量数据由一个考虑光链路和 PNN 设备的模型再现。