caa a22 4500 606204873 CHVBK 20210128101004.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00034-014-9847-9 doi (NATIONALLICENCE)springer-10.1007/s00034-014-9847-9 A Descent Algorithm-Based Parallel Variable Dual Matrix Model and Application to Blind Source Separation [Elektronische Daten] [T.-J. Zeng, Q.-Y. Feng] In this paper, we focus on the problem of blind source separation (BSS). To solve the problem efficiently, a new algorithm is proposed. First, a parallel variable dual-matrix model (PVDMM) that considers all the numerical relations between a mixing matrix and a separating matrix is proposed. Different constrained terms are used to construct the cost function for every sub-algorithm. These constrained terms reflect a numerical relation. Therefore, a number of undesired solutions are excluded, the search region is reduced, and the convergence efficiency of the algorithm is ultimately improved. Parallel sub-algorithms are proven to converge to a separable matrix only if the cost function approaches zero. Second, a descent algorithm (DA) as a PVDMM optimizing approach is proposed in this paper as well. Apparently, the efficiency of the algorithm depends completely on the DA. Unlike the traditional descent method, the DA defines step length by solving inequality instead of merely utilizing the Wolfe- or Armijo-type search rule. Stimulation results indicate that the DA can improve computational efficiency. Under mild conditions, the DA has been proven to have strong convergence properties. Numerical results also show that the method is very efficient and robust. Finally, we applied the combinative algorithm to the BSS problem. Computer simulations illustrate its good performance. Springer Science+Business Media New York, 2014 Blind source separation nationallicence Joint diagonalization nationallicence Parallel variable dual-matrix model nationallicence Descent algorithm nationallicence Zeng T.-J School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China aut Feng Q.-Y School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/1(2015-01-01), 269-300 0278-081X 34:1<269 2015 34 34 https://doi.org/10.1007/s00034-014-9847-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-014-9847-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zeng T.-J School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China aut NATIONALLICENCE 700 1- Feng Q.-Y School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/1(2015-01-01), 269-300 0278-081X 34:1<269 2015 34 34