کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
386932 660893 2009 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Blind source separation with dynamic source number using adaptive neural algorithm
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Blind source separation with dynamic source number using adaptive neural algorithm
چکیده انگلیسی

A difficult blind source separation (BSS) issue dealing with an unknown and dynamic number of sources is tackled in this study. In the past, the majority of BSS algorithms familiarize themselves with situations where the numbers of sources are given, because the settings for the dimensions of the algorithm are dependent on this information. However, such an assumption could not be held in many advanced applications. Thus, this paper proposes the adaptive neural algorithm (ANA) which designs and associates several auto-adjust mechanisms to challenge these advanced BSS problems. The first implementation is the on-line estimator of source numbers improved from the cross-validation technique. The second is the adaptive structure neural network that combines feed-forward architecture and the self-organized criterion. The last is the learning rate adjustment in order to enhance efficiency of learning. The validity and performance of the proposed algorithm are demonstrated by computer simulations, and are compared to algorithms with state of the art. From the simulation results, these have been confirmed that the proposed ANA performed better separation than others in static BSS cases and is feasible for dynamic BSS cases.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 5, July 2009, Pages 8855–8861
نویسندگان
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