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Xinyuan Xia
Hebei University of Technology

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The Oil Layer Recognition Based on Multi-kernel Function Relevance Vector Machines Qianqian Zhao; Xinyuan Xia; Kewen Xia; Zhaozheng Hu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In the oil layer recognition, Relevance vector machines (RVM) have a good effect. But the single kernel function RVM has some limitations, a kind of multi-kernel function RVM based on particle swarm optimization (PSO) is proposed, which includes the model parameter estimation, model optimization on multi-kernel function RVM, PSO-based training, and recognition. The results of simulation experiment for a typical recognition dataset show that its effect is superior to that of classical RVM and PSO-based single kernel function RVM, and its actual application for oil layer recognition in well logging indicates that the recognition results are completely consistent with the conclusions of oil trial, and it has the high recognition accuracy and the good recognition effect. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.4167
Channel Estimation on 60GHz Wireless System Based on Subspace Pursuit Baokai Zu; Xinyuan Xia; Kewen Xia; Chuanjian Bai
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i9.pp6852-6859

Abstract

Due to the channel with characteristic of sparse multi-path in the 60 GHZ wireless communication system, the channel estimation problem can be attributed to that of sparse signals recovery. And with the consideration of the subspace pursuit (SP) algorithm is superior to the orthogonal matching pursuit (OMP) at reconstruction precision, the channel estimation technique based on the SP algorithm is presented in the 60 GHZ wireless communication system, First, design the OFDM multi-carrier modulation communication system. Then, establish the channel estimation mathematical model with indoor Line-of-sight. Finally, complete the reconstruction of sparse signals using SP algorithm. The experimental results and comparison analysis show that the presented technique based on the SP algorithm provides better channel estimation performances in the same pilot conditions, and it is superior to the technique based on OMP algorithm and the technique based on least square (LS) algorithm.
Co-Authors Baokai Zu Chuanjian Bai Kewen Xia Qianqian Zhao Zhaozheng Hu