针对蚁群聚类算法在聚类结果中出现部分数据划分不够准确的问题,提出蚁群聚类改进算法。对已有蚁群聚类算法的结果簇做调整,从而得到更好的聚类结果。使用KDD Cup 1999入侵检测数据集所作的实验结果表明,聚类效果改进明显,入侵检测率有...针对蚁群聚类算法在聚类结果中出现部分数据划分不够准确的问题,提出蚁群聚类改进算法。对已有蚁群聚类算法的结果簇做调整,从而得到更好的聚类结果。使用KDD Cup 1999入侵检测数据集所作的实验结果表明,聚类效果改进明显,入侵检测率有所提高。展开更多
The paper investigates the problem of the design of an optimal Orthogonal Fre- quency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is propose...The paper investigates the problem of the design of an optimal Orthogonal Fre- quency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is proposed. In the proposed method, the Markov Chain Monte Carlo (MCMC) methods are employed for the blind Bayesian detection without channel es- timation. Meanwhile, with the exploitation of the characteristics of OFDM systems, two methods are employed to improve the convergence rate and enhance the efficiency of MCMC algorithms. One is the integration of the posterior distribution function with respect to the associated channel parameters, which is involved in the derivation of the objective distribution function; the other is the intra-symbol differential coding for the elimination of the bimodality problem resulting from the presence of unknown fading channels. Moreover, no matrix inversion is needed with the use of the orthogonality property of OFDM modulation and hence the computational load is significantly reduced. Computer simulation results show the effectiveness of the fast convergent Monte Carlo receiver.展开更多
基金Partially supported by the National Natural Science Foundation of China (No.60172028).
文摘The paper investigates the problem of the design of an optimal Orthogonal Fre- quency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is proposed. In the proposed method, the Markov Chain Monte Carlo (MCMC) methods are employed for the blind Bayesian detection without channel es- timation. Meanwhile, with the exploitation of the characteristics of OFDM systems, two methods are employed to improve the convergence rate and enhance the efficiency of MCMC algorithms. One is the integration of the posterior distribution function with respect to the associated channel parameters, which is involved in the derivation of the objective distribution function; the other is the intra-symbol differential coding for the elimination of the bimodality problem resulting from the presence of unknown fading channels. Moreover, no matrix inversion is needed with the use of the orthogonality property of OFDM modulation and hence the computational load is significantly reduced. Computer simulation results show the effectiveness of the fast convergent Monte Carlo receiver.
