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Spectrum prediction for high-frequency radar based on Extreme Learning Machine

机译:基于极限学习机的高频雷达频谱预测

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In this paper, a new predictive method based on Extreme Learning Machine is proposed to predict the spectrum data obtained from by frequency monitoring system of high-frequency radar. In order to improve the forecasting accuracy and real-time of spectrum prediction of high-frequency radar, Empirical Mode Decomposition method is used for the preprocessing of spectrum data. Based on the simulation environment of MATLAB, compared with the predictive method based on support vector regression, the results show that the proposed method performs better both at forecasting accuracy and speed.
机译:本文提出了一种基于极限学习机的新的预测方法,用于预测由高频雷达的频率监测系统获得的频谱数据。为了提高高频雷达频谱预测的准确性和实时性,采用经验模态分解法对频谱数据进行预处理。在MATLAB的仿真环境下,与基于支持向量回归的预测方法相比,该方法在预测精度和速度上均具有较好的表现。

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