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Modeling of relative intensity noise and terminal electrical noise of semiconductor lasers using artificial neural network

机译:使用人工神经网络对半导体激光器的相对强度噪声和终端电噪声进行建模

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摘要

In this paper, artificial neural network (ANN) is used to predict the source laser’s relative intensity noise (RIN) and the terminal electrical noise (TEN) of semiconductor lasers. For this purpose, the multi-layer perceptron (MLP) neural network trained with the back propagation algorithm is used. To develop this model, the normalized bias current and frequency are selected as the input parameters and the RIN and TEN of semiconductor lasers are selected as the output parameters. The obtained results show that the proposed ANN model is in a good agreement with the numerical method, and a small error between the predicted values and the numerical solution is obtained. Therefore, the proposed ANN model is a useful, reliable, fast and cheap tool to predict the RIN and TEN of semiconductor lasers.
机译:在本文中,人工神经网络(ANN)用于预测源激光器的相对强度噪声(RIN)和半导体激光器的终端电噪声(TEN)。为此,使用经过反向传播算法训练的多层感知器(MLP)神经网络。为了开发该模型,选择归一化的偏置电流和频率作为输入参数,并选择半导体激光器的RIN和TEN作为输出参数。结果表明,所提出的人工神经网络模型与数值方法吻合良好,预测值与数值解之间的误差较小。因此,所提出的人工神经网络模型是预测半导体激光器的RIN和TEN的有用,可靠,快速且廉价的工具。

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