A variable step-size selection method for implicit integration schemes

2006 ◽  
Author(s):  
R. Holsapple ◽  
R. Iyer ◽  
D. Doman
Keyword(s):  
Selection Method ◽  
Variable Step Size ◽  
Implicit Integration ◽  
Step Size ◽  
Size Selection ◽  
Integration Schemes ◽  
Variable Step

A Novel Variable Step-Size Algorithm for Implicit Integration

2011 ◽  
Vol 255-260 ◽  
pp. 2159-2163
Author(s):  
Jian Xiao Zou ◽  
Cui Yun Zhou ◽  
Gang Zheng
Keyword(s):  
Numerical Algorithm ◽  
Variable Coefficient ◽  
Variable Step Size ◽  
Implicit Integration ◽  
Output Variable ◽  
Step Size ◽  
Variable Step ◽  
The Common ◽  
The Difference ◽  
Coefficient Method

A new variable step-size numerical algorithm for implicit integration is discussed in this paper. The scheme for increase and decrease of step size is discussed according to the difference of output variable value. The next step size is calculated through the variable coefficient method and the limitation rules. The convergence and accuracy are testified by the simulation result. Compared with the common used ode45 algorithm, the algorithm has more computing efficiency with a certain calculation precision.

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.

Sign in / Sign up

Export Citation Format

Share Document