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A particle swarm optimization based support vector machine for digital communication equalizers

机译:基于粒子群优化的数字通信均衡器支持向量机

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摘要

The support vector machine (SVM) is a powerful tool for solving problems with high dimensional, nonlinearly, and is of excellent performance for channel equalization in communication systems. In this study, we propose PSO-SVM as channel equalization. To reconstruct the signal that has the inter symbol interference (ISI) and white Gaussian noise which in high speed communications environments. The SVM parameters will affect the identification of the result. Therefore, we use particle swarm optimization (PSO) to find the suit parameters in SVM. The PSO-SVM to realize the Bayesian equalization solution can be achieved efficiently.
机译:支持向量机(SVM)是解决高维非线性问题的有力工具,并且在通信系统中的信道均衡方面具有出色的性能。在这项研究中,我们提出PSO-SVM作为信道均衡。重建在高速通信环境中具有符号间干扰(ISI)和高斯白噪声的信号。 SVM参数将影响结果的识别。因此,我们使用粒子群优化(PSO)在SVM中找到拟合参数。可以有效地实现用于实现贝叶斯均衡解决方案的PSO-SVM。

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