An Adaptive Narrow-Band Filter with Variable Step

2014 ◽  
Vol 644-650 ◽  
pp. 4103-4106
Author(s):  
Da Ming Wang ◽  
Jian Hui Wang ◽  
Wei Jia Cui ◽  
Xu Hui Yang
Keyword(s):  
Steady State ◽  
Convergence Rates ◽  
Transient State ◽  
Learning Rate ◽  
Lms Algorithm ◽  
Low Snr ◽  
Band Filter ◽  
Variable Step ◽  
Narrow Band Filter ◽  
Adaptive Lms

LMS algorithm is a kind of classic adaptive algorithms. Although it has the virtue of simple operation, it also shows the defects of relatively slow convergence and big steady state errors in low SNR. To remedy these defects, this paper put forward a new variable steps adaptive LMS algorithm. In the transient state, the learning rate increases slowly with the iteration times which accelerate the convergence rate of LMS algorithm. In the steady state, the learning rate decreases gradually with the iteration times which guarantee the convergence accuracy of LMS algorithm. After this improved algorithm is applied in the design of adaptive wavetrap, the simulation results show that it can not only effectively ease up the conflicts between convergence rates and steady state errors, but also improve the performance of wavetrap in real-time trapping.

A Novel Variable Step Size LMS Algorithm Based on Modified Hyperbolic Tangent and Its Simulation

2012 ◽  
Vol 490-495 ◽  
pp. 1426-1430 ◽  
Author(s):  
Fu Qing Tian ◽  
Rong Luo
Keyword(s):  
Steady State ◽  
Noise Suppression ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Hyperbolic Tangent ◽  
Step Size ◽  
Low Snr ◽  
Variable Step ◽  
Overall Performance ◽  
Simulation Results

In the paper, a new variable step size LMS algorithm based on modified hyperbolic tangent is presented. In the algorithm, the step size is adjusted by the estimation of the autocorrelation between and .The algorithm introduces the compensation monomial to improve the convergence and the parameters to improve the shape and bottom characteristic of hyperbolic tangent. Therefore, the algorithm has faster convergence, better performance of noise suppression，lower steady state error and misadjustment. The theoretical analysis and simulation results all show that the overall performance of the new algorithm exceeds greatly some existent others under low SNR condition.

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 Variable Step Size LMS Based on Sparsity for System Identification

2013 ◽  
Vol 475-476 ◽  
pp. 1060-1066
Author(s):  
X.Q. Chen ◽  
Hua Ju ◽  
Wei Fan ◽  
W.G. Huang ◽  
Z.K. Zhu
Keyword(s):  
Steady State ◽  
System Identification ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Practical Applications ◽  
Variable Step ◽  
Size Adjustment ◽  
State Error

In many practical applications, the impulse responses of the unknown system are sparse. However, the standard Least Mean Square (LMS) algorithm does not make full use of the sparsity, and the general sparse LMS algorithms increase steady-state error because of giving much large attraction to the small factor. In order to improve the performance of sparse system identification, we propose a new algorithm which introduces a variable step size method into the Reweighted Zero-Attracting LMS (RZALMS) algorithm. The improved algorithm, whose step size adjustment is controlled by the instantaneous error, is called Variable step size RZALMS (V-RZALMS). The variable step size leads to yielding smaller steady-state error on the premise of higher convergent speed. Moreover, the sparser the system is, the better the V-RZALMS performs. Three different experiments are implemented to validate the effectiveness of our new algorithm.

scholarly journals Countermeasure for Interrupted-sampling Repeater Jamming based on Fractional Fourier Transformation

2018 ◽  
Vol 232 ◽  
pp. 03037
Author(s):  
Ming Liu ◽  
Shu Tao ◽  
Qingrong Chen
Keyword(s):  
Fourier Transformation ◽  
Narrow Band ◽  
Operation Time ◽  
Low Complexity ◽  
Interference Signal ◽  
Low Snr ◽  
Band Filter ◽  
Narrow Band Filter ◽  
Specific Order ◽  
Short Operation Time

Today, the interrupted-sampling repeater jamming (ISRJ) has posed a serious threat to LFM radars. In this paper, a countermeasure to suppressing ISRJ based on fractional Fourier transformation (FrFT) is presented. The echo signals, mixed with ISRJ, will be processed in FrFT of specific order, and then a narrow band filter based on parameters of FrFT is designed to extract the target signals and suppress interference signal, so as to realize the target detection. The three kinds of models of ISRJ (ISDRJ, ISRRJ, ISCRJ) are introduced; the anti-jamming principles are analyzed and simulated. The simulation results show that, the algorithm has low complexity and takes short operation time, and it is effective in low SNR or high JSR condition.

scholarly journals Multi-Machine Repairable System with One Unreliable Server and Variable Repair Rate

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1299
Author(s):  
Shengli Lv
Keyword(s):  
Steady State ◽  
Transient State ◽  
Repairable System ◽  
Repair Rate ◽  
Numerical Illustration ◽  
Transform Method ◽  
Unreliable Server ◽  
Busy Time ◽  
The Mean ◽  
Mean Time

This paper analyzed the multi-machine repairable system with one unreliable server and one repairman. The machines may break at any time. One server oversees servicing the machine breakdown. The server may fail at any time with different failure rates in idle time and busy time. One repairman is responsible for repairing the server failure; the repair rate is variable to adapt to whether the machines are all functioning normally or not. All the time distributions are exponential. Using the quasi-birth-death(QBD) process theory, the steady-state availability of the machines, the steady-state availability of the server, and other steady-state indices of the system are given. The transient-state indices of the system, including the reliability of the machines and the reliability of the server, are obtained by solving the transient-state probabilistic differential equations. The Laplace–Stieltjes transform method is used to ascertain the mean time to the first breakdown of the system and the mean time to the first failure of the server. The case analysis and numerical illustration are presented to visualize the effects of the system parameters on various performance indices.

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