کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1713358 | 1013221 | 2006 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Blind source separation of ship-radiated noise based on generalized Gaussian model
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
When the distribution of the sources cannot be estimated accurately, the ICA algorithms failed to separate the mixtures blindly. The generalized Gaussian model (GGM) is presented in ICA algorithm since it can model non-Gaussian statistical structure of different source signals easily. By inferring only one parameter, a wide class of statistical distributions can be characterized. By using maximum likelihood (ML) approach and natural gradient descent, the learning rules of blind source separation (BSS) based on GGM are presented. The experiment of the ship-radiated noise demonstrates that the GGM can model the distributions of the ship-radiated noise and sea noise efficiently, and the learning rules based on GGM gives more successful separation results after comparing it with several conventional methods such as high order cumulants and Gaussian mixture density function.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems Engineering and Electronics - Volume 17, Issue 2, June 2006, Pages 321-325
Journal: Journal of Systems Engineering and Electronics - Volume 17, Issue 2, June 2006, Pages 321-325
نویسندگان
Kong Wei, Yang Bin,