کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
410877 | 679170 | 2006 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Using non-linear even functions for error minimization in adaptive filters
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Using non-linear even functions for error minimization in adaptive filters Using non-linear even functions for error minimization in adaptive filters](/preview/png/410877.png)
چکیده انگلیسی
In this work, we analyze algorithms for adaptive filtering based on non-linear cost function of the error, which we named non-linear even moment (NEM) algorithms. We assume that this non-linear function can be generally described in a Taylor series as a linear combination of the even moments of the error. NEM is a generalization of the well-known least mean square (LMS). We study the NEM convergence behavior and derive equations for misadjustment and convergence. We found a good approximation for the theoretical results and we show that there are various combinations of the even moments which yields better results than the LMS as well as other algorithms proposed in the literature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 70, Issues 1–3, December 2006, Pages 9–13
Journal: Neurocomputing - Volume 70, Issues 1–3, December 2006, Pages 9–13
نویسندگان
Allan Kardec Barros, Jose Principe, Yoshinori Takeuchi, Noboru Ohnishi,