[1] 倪忠. 基于麦克风阵列的语音增强方法研究[D]. 长沙:湖南大学, 2017. [2] 戴华骅, 王亚森, 赵英潇, 等. 一种基于GSC框架波束域快速稳健自适应波束形成算法[J]. 科学技术与工程, 2014, 14(29):39-43. Dai H Y, Wang Y S, Zhao Y X, et al. A fast robust adaptive beam formation algorithm based on GSC frame beam domain[J]. Science Technology and Engineering, 2014, 14(29):39-43. (in Chinese) [3] 刘可. 基于阵列天线的自适应波束形成算法研究[D]. 哈尔滨:哈尔滨工程大学, 2018. [4] 刘春辉, 齐越, 丁文锐, 等. 最大相关熵准则自适应滤波器的分数阶长算法[J]. 北京航空航天大学学报, 2016, 42(2):413-420. Liu C H, Qi Y, Ding W R, et al. Fractional length algorithm for adaptive filters with maximum correlation entropy criteria[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(2):413-420. (in Chinese) [5] 吴鹏, 李晶皎, 王爱侠, 等. 相位匹配噪声估计的高阶谱去噪方法[J]. 小型微型计算机系统, 2010, 31(12):2381-2384. Wu P, Li J J, Wang A X, et al. High-order spectral denoising method for phase matching noise estimation[J]. Journal of Chinese Computer Systems, 2010, 31(12):2381-2384. (in Chinese) [6] 林政剑, 熊美英, 查代奉. 非高斯噪声背景下的诱发电位信号去噪方法[J]. 计算机工程与应用, 2014, 50(9):186-188. Lin Z J, Xiong M Y, Zha D F. Denoising method of evoked potential signal under nonGaussian noise background[J]. Computer Engineering and Applications, 2014, 50(9):186-188. (in Chinese) [7] 李翰芳. 一种新的非高斯分布噪声下的小波去噪方法[J]. 湖北工业大学学报, 2011, 26(2):136-139. Li H F. A new wavelet denoising method under non-Gaussian distributed noise[J]. Journal of Hubei University of Technology, 2011, 26(2):136-139. (in Chinese) [8] 吴文静, 梁中华, 罗倩文, 等. 基于最大相关熵的多凸组合滤波器[J]. 电子技术应用, 2018, 44(12):97-100. Wu W J, Liang Z H, Luo Q W, et al. Multi-convex combined filter based on maximum correlation entropy[J]. Application of Electronic Technique, 2018, 44(12):97-100. (in Chinese) [9] 李思齐. 改进的麦克风阵列语音增强GSC算法研究[D]. 海口:海南大学, 2016. [10] 赵益波, 杨蕾, 严涛, 等. 麦克风阵列的协同自适应滤波语音增强方法[J]. 现代电子技术, 2019, 42(8):16-20. Zhao Y B, Yang L, Yan T, et al. Collaborative adaptive filtering speech enhancement method for microphone array[J]. Modern Electronics Technique, 2019, 42(8):16-20. (in Chinese) [11] 罗丁利, 徐伟. 一种阻塞矩阵的构建方法[J]. 火控雷达技术, 2009, 38(4):53-56. Luo D L, Xu W. A method of constructing blocking Matrix[J]. Fire Control Radar Technology, 2009, 38(4):53-56. (in Chinese) [12] Giffithsl J, Jim C W. An alternative approach to linearly constrained adaptive beamforming[J]. IEEE Transactions on Antennas and Propagation, 1982, 30(1):27-34. [13] 徐进, 赵益波, 郭业才. 一种新的麦克风阵列自适应语音增强方法[J]. 应用科学学报, 2015, 33(2):187-193. Xu J, Zhao Y B, Guo Y C. A new adaptive speech enhancement method for microphone array[J]. Journal of Applied Sciences, 2015, 33(2):187-193. (in Chinese) [14] Liu S H, Ma Y H, Huang Y M. Sea clutter cancellation for passive radar sensor exploiting multi-channel adaptive filters[J]. IEEE Sensors Journal, 2019, 19(3):982-995. [15] Scariniti M, Comminiello D, Parisi R, et al. Nonlinear spline adaptive filtering[J]. Signal Processing, 2013, 93(4):772-783. [16] Peng S Y, Wu Z Z, Zhang X, et al. Nonlinear spline adaptive filtering under maximum correntropy criterion[C]//Tencon IEEE Region 10 Conference. IEEE, 2016. [17] Singh A, Principe J C. Using correntropy as a cost function in linear adaptive filters[C]//International Joint Conferences on Neural Networks. IEEE, 2009:2950-2955. [18] 姜骁, 马文涛, 曲桦. 时域和酉空间中基于最大相关熵准则的非线性噪声处理[J]. 计算机应用, 2012, 32(12):3287-3290. Jiang X, Ma W T, Qu H. Nonlinear noise processing based on maximum correntropy criterion in time domain and unitary space[J]. Journal of Computer Applications, 2012, 32(12):3287-3290. (in Chinese) [19] 石嘉豪. 基于最大互相关熵的核自适应滤波算法研究[D]. 广州:华南理工大学, 2016. [20] 刘春丽, 邵雷, 陈海龙, 等. 标准参数下Alpha稳定分布随机变量的产生及仿真[J]. 哈尔滨理工大学学报, 2014, 19(3):51-56. Liu C L, Shao L, Chen H L, et al. Generation and simulation of alpha stable distributed random variables under standard parameters[J]. Journal of Harbin University of Science and Technology, 2014, 19(3):51-56. (in Chinese) |