Two Stage Step-size Scaler Adaptive Filter Design for ECG Denoising

Author(s):  
Priyank H. Prajapati ◽  
Anand D. Darji
Author(s):  
Weilin Nie ◽  
Cheng Wang

Abstract Online learning is a classical algorithm for optimization problems. Due to its low computational cost, it has been widely used in many aspects of machine learning and statistical learning. Its convergence performance depends heavily on the step size. In this paper, a two-stage step size is proposed for the unregularized online learning algorithm, based on reproducing Kernels. Theoretically, we prove that, such an algorithm can achieve a nearly min–max convergence rate, up to some logarithmic term, without any capacity condition.


2003 ◽  
Vol 36 (5) ◽  
pp. 645-650 ◽  
Author(s):  
D. Theilliol ◽  
M. Rodrigues ◽  
M. Adam-Medina ◽  
D. Sauter

2011 ◽  
Vol 50 (2) ◽  
pp. 142-149 ◽  
Author(s):  
Rahmat Allah Hooshmand ◽  
Mahdi Torabian Esfahani

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 199025-199033 ◽  
Author(s):  
Taesu Park ◽  
Minho Lee ◽  
Poogyeon Park

Sign in / Sign up

Export Citation Format

Share Document