spectrum期刊最新论文

L. Huang*, C. Qian, . So and J. Fang, “Shrinkage-based source enumeration for large array and small samples” IEEE Transactions on Aerospace and Electronic Systems, 2014, to appear. (Regular Paper） . He, . Shi, L. Huang* and H. C. So, “Underdetermined DOA estimation for wideband signals using robust sparse covariance fitting” IEEE Signal Processing Letters, in press 2014, to appear. L. Huang*, C. Qian, Y. Xiao and . Zhang, “Performance analysis of volume-based spectrum sensing for cognitive radio,” IEEE Transactions on Wireless Communications, vol. 8, no. 99, pp. 1-14, Aug. 2014, DOI: (Regular Paper) J. Lv, L. Huang*, Y. Shi and X. Fu, “Inversed synthetic aperture radar imaging via modified smoothed ell_0 norm,” IEEE Antenna and Wireless Propagation Letters. vol. 13, no. 1, Jun. 2014, DOI: M. Cao, L. Huang* and C. Qain, “Underdetermined DOA estimation of quasi-stationary signals via Khatri-Rao structure for uniform circular array” Signal Processing, , , , Jan. 2015 (Regular Paper） C. Qian, L. Huang*, . Zeng, and . So, “Direction-of-arrival estimation for coherent signals without knowledge of source number,” IEEE Sensor Journal, vol. 14, no. 9, , Sep. 2014 (Regular Paper） L. Huang*, . So and C. Qian, “Volume-based method for spectrum sensing” Digital Signal Processing, vol. 28, pp. 48-56, May 2014. (Regular Paper） C. Qian, L. Huang* and . So, “Improved unitary root-MUSIC for DOA estimation based on pseudo-noise resampling,” IEEE Signal Processing Letters, vol. 21, no. 2, pp. 140-144, Feb. 2014. C. Qian, L. Huang* and . So, “Computationally efficient ESPRIT algorithm for direction-of-arrival estimation based on Nystrom method,” Signal Processing, vol. 94, pp. 74-80, January 2014. (Regular Paper） , , L. Huang* and . Huang, Underdetermined direction-of-departure and direction-of-arrival estimation in bistatic multiple-input multiple-output radar, Signal Processing, , , , November 2014 W. Sun, . So, . Chan, . Huang and L. Huang*, “Approximate subspace- basediterativeadaptiveapproachforfasttwo-dimensionalspectralestimation,” IEEE Transactions on Signal Processing, , , , Jun. 2014 (Regular Paper） J. Fang, X. Li, H. Li, and L. Huang, “Precoding for decentralized detection of unknown deterministic signals in multisensor systems” IEEE Transactions on Aerospace and Electronic Systems, 2014, to appear (Regular Paper） Z. He, Z. Shi, and L. Huang*, “Covariance sparsity-aware DOA estimation for nonuniform noise,” Digital Signal Processing, vol. 28, pp. 75-81, May 2014. (Regular Paper） L. Huang* and . So, “Source enumeration via MDL criterion based on linear shrinkage estimation of noise subspace covariance matrix,” IEEE Transactions on Signal Processing, vol. 61, no. 19, , Oct. 2013. (Regular Paper). . Zeng, . So and L. Huang*, “lp-MUSIC: Robust direction-of-arrival estimator for impulsive noise environments,” IEEE Transactions on Signal Processing, , , , September 2013. (Regular Paper） W. Sun, . So, . Chan and L. Huang*, “Tensor approach for eigenvector-based multi-dimensional harmonic retrieval,” IEEE Transactions on Signal Processing, , no. 13, pp. 3378-3388, April, 2013. (Regular Paper） K. Liu, . Cost, . So and L. Huang, “Subspace techniques for multidimensional model order selection in colored noise,” Signal Processing, vol. 93, no. 7, pp. 1976-1987, July 2013. (Regular Paper) K. Liu, . So, . Cost, F. Romer and L. Huang*, “Efficient source enumeration for accurate direction-of-arrival estimation in threshold region,” Digital Signal Processing, vol. 23, no. 5, pp. 1668–1677, Sep. 2013. (Regular Paper） . Huang, Y. Wu, . So, Y. Zhang and L. Huang, “Multidimensional sinusoidal frequency estimation using subspace and projection separation approaches,” IEEE Transactions on Signal Processing, vol. 60, no. 10, pp. 5536-5543, Oct. 2012. L. Huang*, . Zhang and . Cheng, “Information theoretic criterion for stopping turbo iteration,” IEEE Transactions on Signal Processing, vol. 59, no. 2, pp. 848-853, Feb. 2011. L. Huang*, T. Long, E. Mao and . So, “MMSE-based MDL method for robust estimation of number of sources without eigendecomposition,” IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 4135-4142, Oct. 2009. L. Huang*, T. Long, E. Mao and . So, “MMSE-based MDL method for accurate source number estimation,” IEEE Signal Processing Letters, vol. 16, no. 9, pp. 798-801, Sep. 2009. L. Huang*, T. Long and S. Wu, “Source enumeration for high-resolution array processing using improved Gerschgorin radii without eigendecomposition,” IEEE Transactions on Signal Processing, vol. 56, no. 12, pp. 5916-5925, Dec. 2008. (Regular Paper) L. Huang*, S. Wu and X. Li, “Reduced-rank MDL method for source enumeration in high-resolution array processing,” IEEE Transactions on Signal Processing, vol. 55, no. 12, pp. 5658-5667, Dec. 2007.( Regular Paper) L. Huang* and S. Wu, “Low-complexity MDL method for accurate source enumeration,” IEEE Signal Processing Letters, vol. 14, no. 9, pp. 581-584, Sep. 2007. L. Huang*, S. Wu, D. Feng, and L. Zhang, “Low complexity method for signal subspace fitting,” IEE Electronics Letters, vol. 40, no. 14, July 2004. L. Huang*, S. Wu, L. Zhang and D. Feng, “Computationally efficient direction-of-arrival estimation based on partial a priori knowledge of signal sources,” EURASIP Journal on Applied Signal Processing, vol. 2006, pp. 1-7, 2006. (Regular Paper) L. Huang*, S. Wu and E. Mao, “Recursion subspace-based method for bearing estimation: a comparative study,” Chinese Journal of Electronics, no. 3, pp. 477-480, July 2010. L. Huang*, D. Feng, S. Wu and L. Zhang, “Computationally efficient method of signal subspace fitting for direction-of-arrival estimation,” IEICE Transactions on Communications, vol. 88, Aug. 2005, pp. 3408-3415. (Regular Paper)

陈梦涵(1994-),女,安徽怀宁人,管理学博士、讲师,主要研究兴趣为绩效评价、决策分析。目前已在SCI期刊《Computers & Industrial Engineering》、《OR Spectrum》发表论文三篇。做好自我规划，因此她始终保持端正的学习态度并明确学习目标，脚踏实地、埋头苦干，积极向老师、同学请教。三年以来，她每学期的综合成绩都位居班级前列，获得校级特等奖学金一次、一等奖学金一次、二等奖学金三次，并获得校级“三好学生”“优秀学生干部”“优秀团员”等荣誉称号。此外，陈梦涵同学已顺利通过了英语四级和六级、计算机二级、

This paper first introduces the basic knowledge of DFT and spectrum analysis, introduces the "fence" effect and the computation of FFT analysis, understanding the FFT algorithm in MATLAB. This paper reviewed the commonly used method to estimate the frequency, including the maximum quasi likelihood algorithm, Rife algorithm and modified Rife, the MUSIC algorithm. This paper finally put forward with the ratio of discrete spectrum correction method to estimate signal frequency amplitude and phase Angle, the computer simulation analysis with MATLAB, use ratio correction method estimate signal frequency amplitude and phase of its high precision, small error, implementation is simple and convenient.