کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
408003 | 678242 | 2011 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Cyclic maximization of non-Gaussianity for blind signal extraction of complex-valued sources
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Cyclic maximization of non-Gaussianity for blind signal extraction of complex-valued sources Cyclic maximization of non-Gaussianity for blind signal extraction of complex-valued sources](/preview/png/408003.png)
چکیده انگلیسی
This article presents a new algorithm for the blind extraction of communications sources (complex-valued sources) through the maximization of negentropy approximations based on nonlinearities. A criterion based on the square modulus of a nonlinearity of the output is used. We decouple the arguments of the criterion so that the algorithm maximizes it cyclically with respect to each argument by means of the Cauchy–Schwarz inequality. A proof of the ascent of the objective function after each iteration is also provided. Numerical simulations corroborate the good performance of the proposed algorithm in comparison with the existing methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 2867–2873
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 2867–2873
نویسندگان
Iván Durán-Díaz, Sergio Cruces, María Auxiliadora Sarmiento-Vega, Pablo Aguilera-Bonet,