MIMO system can provide higher capacity in independent conditions. When the spatial-temporal fading correlation exists, the capacity may decrease. In this paper, the geometrical MIMO channel model is presented with Ri...MIMO system can provide higher capacity in independent conditions. When the spatial-temporal fading correlation exists, the capacity may decrease. In this paper, the geometrical MIMO channel model is presented with Rician factor. Based on the MIMO ergodic capacity, the capacity bounds are derived with arbitrary finite number of antennas. The bounds are derived in the exact expressions in doubly correlated MIMO R/clan channel. Then a simple expression for the capacity bounds is attained for the high SNR. Finally, the tightness of derived bounds is verified by Monte Carlo simulation.展开更多
To simulate a multivariate density with multi_hump, Markov chainMonte Carlo method encounters the obstacle of escaping from one hump to another, since it usually takes extraordinately long time and then becomes practi...To simulate a multivariate density with multi_hump, Markov chainMonte Carlo method encounters the obstacle of escaping from one hump to another, since it usually takes extraordinately long time and then becomes practically impossible to perform. To overcome these difficulties, a reversible scheme to generate a Markov chain, in terms of which the simulated density may be successful in rather general cases of practically avoiding being trapped in local humps, was suggested.展开更多
Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size n.To address this issue,the autho...Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size n.To address this issue,the authors propose a ridge-forward quadratic discriminant(RFQD) analysis method via screening relevant predictors in a successive manner to reduce misclassification rate.The authors use extended Bayesian information criterion to determine the final model and prove that RFQD is selection consistent.Monte Carlo simulations are conducted to examine its performance.展开更多
基金Acknowledgements This work was supported by National 13asie Research Program of China （2009CB320401）, National Natural Science Foundation of China （60972075, 61072055）, Key Scientific and Technologi- cal Project of China 2010ZX03003-003-01, and Fundamental Research Funds for the Central Universities （2009RC0116）.
文摘MIMO system can provide higher capacity in independent conditions. When the spatial-temporal fading correlation exists, the capacity may decrease. In this paper, the geometrical MIMO channel model is presented with Rician factor. Based on the MIMO ergodic capacity, the capacity bounds are derived with arbitrary finite number of antennas. The bounds are derived in the exact expressions in doubly correlated MIMO R/clan channel. Then a simple expression for the capacity bounds is attained for the high SNR. Finally, the tightness of derived bounds is verified by Monte Carlo simulation.
文摘To simulate a multivariate density with multi_hump, Markov chainMonte Carlo method encounters the obstacle of escaping from one hump to another, since it usually takes extraordinately long time and then becomes practically impossible to perform. To overcome these difficulties, a reversible scheme to generate a Markov chain, in terms of which the simulated density may be successful in rather general cases of practically avoiding being trapped in local humps, was suggested.
基金supported by the National Natural Science Foundation of China under Grant No.11401391
文摘Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size n.To address this issue,the authors propose a ridge-forward quadratic discriminant(RFQD) analysis method via screening relevant predictors in a successive manner to reduce misclassification rate.The authors use extended Bayesian information criterion to determine the final model and prove that RFQD is selection consistent.Monte Carlo simulations are conducted to examine its performance.
