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机译:数据驱动稀疏学习的水下声OFDM信道估计稀疏恢复算法的比较
Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, United States;
Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, United States;
Department of Electrical and Computer Engineering, 371 Fairfield Way Unit-4157, University of Connecticut, Storrs, CT 06269-4157, United States;
Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, MI 49931, United States;
LSI Corporation, San Jose, CA 95131, United States;
Sparse channel estimation; Data-driven sparsity learning; Regularization parameter; Compressed sensing; Underwater acoustic communication; OFDM;
机译:基于信道预测的时间多稀疏贝叶斯学习,用于快速时变水下声学OFDM通信中的信道估计
机译:基于稀疏恢复算法的水下声信道估计
机译:双重聚焦:一种新的稀疏信道估计算法,适用于基于双重选择性的基于SFBC-OFDM水下声学系统
机译:水下声OFDM中稀疏信道估计的基本追踪算法比较
机译:稀疏性在自然声源和声通道参数联合估计中的应用
机译:基于贝叶斯学习的聚类稀疏信道估计用于时变水下声学OFDM通信
机译:水下声OFDM中稀疏信道估计的基本追踪算法比较