scholarly journals Variable step size predictor design for a class of linear discrete-time censored system

2021 ◽  
Vol 6 (10) ◽  
pp. 10581-10595
Author(s):  
Zhifang Li ◽  
◽  
Huihong Zhao ◽  
Hailong Meng ◽  
Yong Chen ◽  
...  
Keyword(s):  
Empirical Analysis ◽  
Censored Data ◽  
Discrete Time ◽  
Design Method ◽  
Error Variance ◽  
Variable Step Size ◽  
Step Size ◽  
Measurement Equation ◽  
Variable Step ◽  
The One

<abstract> <p>We propose a novel variable step size predictor design method for a class of linear discrete-time censored system. We divide the censored system into two parts. The system measurement equation in one part doesn't contain the censored data, and the system measurement equation in the other part is the censored signal. For the normal one, we use the Kalman filtering technology to design one-step predictor. For the one that the measurement equation is censored, we determine the predictor step size according to the censored data length and give the gain compensation parameter matrix $β(\mathfrak{s})$ for the case predictor with obvious errors applying the minimum error variance trace, projection formula, and empirical analysis, respectively. Finally, a simulation example shows that the variable step size predictor based on empirical analysis has better estimation performance.</p> </abstract>

A Variable Step-Size for Sparse Nonlinear Adaptive Filters

2021 ◽  
Author(s):  
Alberto Carini ◽  
Markus V. S. Lima ◽  
Hamed Yazdanpanah ◽  
Simone Orcioni ◽  
Stefania Cecchi
Keyword(s):  
Adaptive Filters ◽  
Variable Step Size ◽  
Step Size ◽  
Variable Step

Active control for vehicle interior noise using the improved iterative variable step-size and variable tap-length LMS algorithms

2019 ◽  
Vol 67 (6) ◽  
pp. 405-414 ◽  
Author(s):  
Ningning Liu ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Hui Guo ◽  
Bin Gao ◽  
...  
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Convergence Speed ◽  
Interior Noise ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Vehicle Interior ◽  
Vehicle Interior Noise ◽  
Variable Step

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

A smoothing variable step size algorithm

2006 ◽  
Author(s):  
Yan Huo ◽  
Li Fu ◽  
Tao Jing ◽  
Yu-min Feng
Keyword(s):  
Variable Step Size ◽  
Step Size ◽  
Variable Step

Performance Analysis for Acoustic Echo Cancellation Systems based on Variable Step Size NLMS algorithms

2011 ◽  
Author(s):  
Rajeshwari Hegde ◽  
K. Balachandra ◽  
Madhusudhan Rao ◽  
R. B. Patel ◽  
B. P. Singh
Keyword(s):  
Performance Analysis ◽  
Echo Cancellation ◽  
Variable Step Size ◽  
Acoustic Echo Cancellation ◽  
Step Size ◽  
Variable Step ◽  
Acoustic Echo
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