Complex-Valued Random Fourier Geometric Algebra Adaptive Filtering

被引:4
作者
Huang, Gangyi [1 ]
Shen, Minglin [1 ]
Lin, Dongyuan [1 ]
Qi, Letian [1 ]
Qian, Junhui [2 ,3 ]
Wang, Shiyuan [1 ]
机构
[1] Southwest Univ, Coll Elect & Informat Engn, Chongqing Key Lab Nonlinear Circuits & Intelligen, Chongqing 400715, Peoples R China
[2] Chongqing Univ, Sch Microelect & Commun Engn, Chongqing 400044, Peoples R China
[3] Chongqing Univ, Chongqing Key Lab Biopercept & Intelligent Inform, Chongqing 400044, Peoples R China
基金
中国国家自然科学基金;
关键词
Algebra; Adaptive systems; Kernel; Blades; Transforms; Radial basis function networks; Information processing; Fixed dimensional adaptive filter; complex-valued signals; geometric algebra; random fourier features mapping;
D O I
10.1109/TCSII.2022.3142167
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The complex-valued fixed dimensional adaptive filters (CFDAFs) can improve the performance and computational efficiency of complex-valued kernel adaptive filters (CKAFs), but have the challenge of over-coupling for the real and imaginary parts of complex-valued signals. To this end, this brief proposes a novel fixed dimensional adaptive filter for complex-valued signals named complex-valued random Fourier geometric algebra least mean square (CRFGALMS). On the basis of the framework of geometric algebraic adaptive filtering, the real and imaginary parts of complex-valued signals are mapped into random Fourier features space (RFFS) to improve the efficiency of the nonlinear mapping for complex-valued signals, respectively. The proposed random Fourier feature mapping based on the geometric algebra is endowed with superior presentation abilities in complex-valued domain as it can decouple the nonlinear mapping of the real and imaginary parts of complex-valued signals, efficiently. Simulations on nonlinear channel equalization are used to illustrate the superiority of the proposed CRFGALMS algorithm in terms of dimensionality and filtering performance.
引用
收藏
页码:2346 / 2350
页数:5
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