کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410532 679149 2009 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Signal denoising in engineering problems through the minimum gradient method
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Signal denoising in engineering problems through the minimum gradient method
چکیده انگلیسی

This paper applies the minimum gradient method (MGM) to denoise signals in engineering problems. The MGM is a novel technique based on the complexity control, which defines the learning as a bi-objective problem in such a way to find the best trade-off between the empirical risk and the machine complexity. A neural network trained with this method can be used to pre-process data aiming at increasing the signal-to-noise ratio (SNR). After training, the neural network behaves as an adaptive filter which minimizes the cross-validation error. By applying the general singular value decomposition (GSVD), we show the relation between the proposed approach and the Wiener filter. Some results are presented, including a toy example and two complex engineering problems, which prove the effectiveness of the proposed approach.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 72, Issues 10–12, June 2009, Pages 2270–2275
نویسندگان
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