scholarly journals Optimal convergence speed of Bergman metrics on symplectic manifolds

2020 ◽  
Vol 18 (4) ◽  
pp. 1091-1126
Author(s):  
Wen Lu ◽  
Xiaonan Ma ◽  
George Marinescu
Keyword(s):  
Symplectic Manifolds ◽  
Convergence Speed ◽  
Optimal Convergence ◽  
Bergman Metrics

scholarly journals Adapting Predictive Feedback Chaos Control for Optimal Convergence Speed

2012 ◽  
Vol 11 (4) ◽  
pp. 1310-1324 ◽  
Author(s):  
Christian Bick ◽  
Marc Timme ◽  
Christoph Kolodziejski
Keyword(s):  
Chaos Control ◽  
Convergence Speed ◽  
Optimal Convergence

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.

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