Kernel Adaptive Filters With Feedback Based on Maximum Correntropy

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Kernel recursive maximum correntropy

Zongze Wu 1 , Jiahao Shi 1 , Xie Zhang 1 , Wentao Ma 2 , Badong Chen 2* , Senior Member, IEEE 1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China 2. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China * Fax: 86-29-82668672,Tel:86-29-82668802 ext. 8009, [email protected] Abstract—I...

متن کامل

Constrained maximum correntropy adaptive filtering

Constrained adaptive filtering algorithms inculding constrained least mean square (CLMS), constrained affine projection (CAP) and constrained recursive least squares (CRLS) have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises....

متن کامل

Adaptive beamforming method based on recursive maximum correntropy in impulsive noise with alpha-stable process

As a well-established adaptation criterion, the maximum correntropy criterion (MCC) has been receiving increasing attention due to its robust against outliers. In this paper, a new complex recursive maximum correntropy (CRMC) algorithm without any priori information on the noise characteristics, is proposed under the MCC. The proposed algorithm is useful for adaptive beamforming, when the desir...

متن کامل

Maximum Correntropy Kalman Filter

—Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption. However, when the signals are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive noises, the performance of KF will deteriorate seriously. To improve the robustness of KF against impulsive noises, we propose in ...

متن کامل

Regularized maximum correntropy machine

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the cl...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Access

سال: 2018

ISSN: 2169-3536

DOI: 10.1109/access.2018.2808218