基于最小二乘支持向量机的无线网络信道检测

为了获得理想的无线网络信息检测结果，提出了基于最小二乘支持向量机的无线网络信道机制.首先对当前无线网络信道检测的研究现状进行分析，并建立无线网络信道检测的假设模型，然后采用最小二乘支持向量机构建无线网络信道检测模型，并通过粒子群算法对最小二乘支持向量机参数进行优化，最后在Matlab 2014平台上进行了无线网络信道检测的仿真实验，以验证无线网络信道检测的有效性.结果表明，最小二乘支持向量机获得了高精度的无线网络信道检测结果，无线网络的数据传输成功率得以改善，大幅度降低了数据传输的误码率，在相同实验条件下，无线网络信道检测结果明显高于当前经典检测机制，验证本文机制的优越性.

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

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.