Channel Detection of Wireless Networks Based on Least Squares Support Vector Machines
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    Abstract:

    In order to obtain the ideal wireless network information detection results, a wireless network channel mechanism based on Least Squares Support Vector Machines (LSSVM) is proposed. Firstly, the research on the current situation of wireless network channel detection is analyzed, and the hypothesis model of wireless network channel detection is established. Then, using the least squares support vector construction of wireless network channel detection model, the particle swarm algorithm of LSSVM parameters are optimized. Finally, the wireless network channel detection experiments on MATLAB 2014 platform are performed in order to verify the effectiveness of the wireless network channel detection. The results show that the LSSVM for the wireless network channel achieves high precision detection results, the wireless network data transmission success rate is improved, and the error rate of data transmission is greatly reduced. Under the same experimental conditions, the wireless network channel detection results are significantly higher than that of the current classical detection mechanism, which verifies the superiority of the proposed model.

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周向军.基于最小二乘支持向量机的无线网络信道检测.计算机系统应用,2018,27(5):151-155

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History
  • Received:August 23,2017
  • Revised:September 12,2017
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  • Online: April 23,2018
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