scholarly journals Spectrogram Image Analysis of Error Signals for Minimizing Impulse Noise

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jeakwan Kim ◽  
Yunseon Choi ◽  
Young-Sup Lee
Keyword(s):  
Image Analysis ◽  
Impulse Noise ◽  
Active Noise Control ◽  
Convergence Speed ◽  
New Method ◽  
Least Mean Square ◽  
Real Time Control ◽  
Step Size ◽  
Time Control ◽  
Analysis Of Error

This paper presents the theoretical and experimental study on the spectrogram image analysis of error signals for minimizing the impulse input noises in the active suppression of noise. Impulse inputs of some specific wave patterns as primary noises to a one-dimensional duct with the length of 1800 mm are shown. The convergence speed of the adaptive feedforward algorithm based on the least mean square approach was controlled by a normalized step size which was incorporated into the algorithm. The variations of the step size govern the stability as well as the convergence speed. Because of this reason, a normalized step size is introduced as a new method for the control of impulse noise. The spectrogram images which indicate the degree of the attenuation of the impulse input noises are considered to represent the attenuation with the new method. The algorithm is extensively investigated in both simulation and real-time control experiment. It is demonstrated that the suggested algorithm worked with a nice stability and performance against impulse noises. The results in this study can be used for practical active noise control systems.

Active Noise Control Based on TMS320C5509

2013 ◽  
Vol 631-632 ◽  
pp. 1172-1176
Author(s):  
Yong Wei Ma ◽  
Xin Ke Gou ◽  
Xian Jun Du ◽  
Chong Yu Ren
Keyword(s):  
Control System ◽  
Real Time ◽  
Noise Control ◽  
Active Noise Control ◽  
Noise Cancellation ◽  
Real Time Control ◽  
Time Control ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
Mixed Language

The feed-forward adaptive active noise control (AANC) system is presented. Firstly, the hardware project of the system is brought forward, by selecting TMS320C5509 DSP as the controller. Then, using the mixed language, the active noise real-time control system is realized, based on the FXLMS algorithm. It’s proved that a good noise cancellation is achieved by the experiment.

Image analysis for maintenance of coating quality in nickel electroplating baths – Real time control

2011 ◽  
Vol 706 (1) ◽  
pp. 1-7 ◽  
Author(s):  
M. Vidal ◽  
J.M. Amigo ◽  
R. Bro ◽  
F. van den Berg ◽  
M. Ostra ◽  
...  
Keyword(s):  
Image Analysis ◽  
Real Time ◽  
Real Time Control ◽  
Coating Quality ◽  
Time Control ◽  
Nickel Electroplating

Improved Adaptive Beamforming for Smart Antennas

2021 ◽  
Author(s):  
Veerendra Dakulagi ◽  
Rohini Dakulagi ◽  
Kim Ho Yeap ◽  
Humaira Nisar
Keyword(s):  
Smart Antenna ◽  
Adaptive Beamforming ◽  
New Method ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
High Data ◽  
Array Configuration ◽  
Least Mean Square Algorithm ◽  
Normalized Lms

Abstract In this paper, we propose a new antenna array configuration for smart antenna beamforming. In this new method, we displace two antenna elements of a uniform linear array (ULA) and place them at the top and bottom of the array axis. We investigate the efficacy of this method by deploying the variable step size least mean square algorithm (VSSLMS). The proposed method is compared with popular LMS and normalized LMS algorithms. Computer simulations show that the proposed method has enhanced convergence rate and high data transmission compared to the LMS and the NLMS methods. Also, the new method has the same performance for middle angles, near boresight and array endfires which is not possible for the LMS and the NLMS method using a ULA.

Image Analysis Based Real Time-Control of Glucose Concentration

2005 ◽  
pp. 589-592 ◽  
Author(s):  
T. Brueckerhoff ◽  
J.-G. Frerichs ◽  
K. Joeris ◽  
K. Konstantinov ◽  
T. Scheper
Keyword(s):  
Image Analysis ◽  
Real Time ◽  
Glucose Concentration ◽  
Real Time Control ◽  
Time Control

scholarly journals A Novel Self-Interference Cancellation Method Using an Optimized LMS Algorithm in CCFD Systems for a 5G Communication Network

2019 ◽  
Vol 9 (16) ◽  
pp. 3308
Author(s):  
Zeng-You Sun ◽  
Yu-Jie Zhao
Keyword(s):  
Wireless Communication ◽  
Interference Cancellation ◽  
Convergence Speed ◽  
Lms Algorithm ◽  
Full Duplex ◽  
Time Varying ◽  
Least Mean Square ◽  
Step Size ◽  
Channel Tracking ◽  
Step Factor

The Co-frequency Co-time Full Duplex (CCFD) is a key concept in 5G wireless communication networks. The biggest challenge for CCFD wireless communication is the strong self-interference (SI) from near-end transceivers. Aiming at cancelling the SI of near-end transceivers in CCFD systems in the radio frequency (RF) domain, a novel time-varying Least Mean Square (LMS) adaptive filtering algorithm which is based on step-size parameters gradually decrease with time varying called the DTV-LMS algorithm is proposed in this paper. The proposed DTV-LMS algorithm in this paper establishes the non-linear relationship between step factor and the evolved arct-angent function, and using the relationship between the time parameter and error signal correlation value to coordinately control the step factor to be updated. This algorithm maintains a low computational complexity. Simultaneously, the DTV-LMS algorithm can also attain the ideal characteristics, including the interference cancellation ratio (ICR), convergence speed, and channel tracking, so that the SI signal in the RF domain of a full duplex system can be effectively cancelled. The analysis and simulation results show that the ICR in the RF domain of the proposed algorithm is higher than that in the compared algorithms and have a faster convergence speed. At the same time, the channel tracking capability has also been significantly enhanced in CCFD systems.

scholarly journals Variable step-size LMS adaptive filters for CDMA multiuser detection

2004 ◽  
Vol 17 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Karen Egiazarian ◽  
Pauli Kuosmanen ◽  
Ciprian Bilcu
Keyword(s):  
Multiuser Detection ◽  
Adaptive Filters ◽  
Convergence Speed ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Trade Off ◽  
Variable Step ◽  
Code Division Multiple

Due to its simplicity the adaptive Least Mean Square (LMS) algorithm is widely used in Code-Division Multiple access (CDMA) detectors. However its convergence speed is highly dependent on the eigen value spread of the input covariance matrix. For highly correlated inputs the LMS algorithm has a slow convergence which require long training sequences and therefore low transmission speeds. Another drawback of the LMS is the trade-off between convergence speed and steady-state error since both are controlled by the same parameter, the step-size. In order to eliminate these drawbacks, the class of Variable Step-Size LMS (VSSLMS) algorithms was introduced. In this paper, we study the behavior of some algorithms belonging to the class of VSSLMS for training based multiuser detection in a CDMA system. We show that the proposed Complementary Pair Variable Step-Size LMS algorithms highly increase the speed of convergence while reducing the trade-off between the convergence speed and the output error.

A Joint Optimized Robust Acoustic Echo Cancellation Algorithm

2019 ◽  
Vol 33 (09) ◽  
pp. 1959029 ◽  
Author(s):  
Hongyan Li ◽  
Jianghao Feng ◽  
Yue Wang ◽  
Xueying Zhang
Keyword(s):  
Impulse Noise ◽  
Regularization Parameter ◽  
Convergence Speed ◽  
Echo Cancellation ◽  
Acoustic Echo Cancellation ◽  
Time Varying ◽  
Mean Square ◽  
Least Mean Square ◽  
Acoustic Echo ◽  
Series Of Experiments

When the input signals for acoustic echo cancellation (AEC) are related signals, the convergence speed of the traditional normalized least mean square (NLMS) algorithms is significantly reduced. In this paper, a joint optimization robust AEC algorithm is proposed to solve this problem. Based on the analysis of the convergence of the normalized subband adaptive filtering (NSAF) algorithm, the algorithm is optimized by minimizing the mean square error (MSE) of the NSAF algorithm, combining sub-band time-varying step factor and time-varying regularization parameter to update the filter weight vectors. And when the impulse noise occurs, the sub-band cut-off parameter is updated in a recursive manner, which makes the algorithm achieve fast convergence speed and low steady-state error, and has strong robustness to impulse noise. In a series of experiments on AEC, simulation results show that the performance of the algorithm is better than the existing algorithms.

scholarly journals A Time-Efficient Method for Determining an Optimal Scaling Factor and the Encoder Resolution in the Multichannel FXECAP-L Algorithm with Evolving Order for Active Noise Control

2019 ◽  
Vol 9 (3) ◽  
pp. 560 ◽  
Author(s):  
Ángel Vázquez ◽  
Xochitl Maya ◽  
Juan Avalos ◽  
Giovanny Sánchez ◽  
Juan Sánchez ◽  
...  
Keyword(s):  
Noise Control ◽  
Rapid Development ◽  
Active Noise Control ◽  
Computational Cost ◽  
Scaling Factor ◽  
Convergence Speed ◽  
Least Mean Square ◽  
Automatic Adjustment ◽  
Affine Projection ◽  
Active Noise

Affine projection (AP) algorithms have demonstrated faster convergence speed than conventional least mean square (LMS) algorithms, thus providing an attractive solution in the active noise control (ANC) field. However, the AP algorithms demand high computational cost, restricting their practical use in real-time ANC applications. Recently, a multichannel filtered-x error-coded affine projection-like (FXECAP-L) algorithm with evolving order has been proposed to reduce the computational burden by maintaining the convergence speed of AP algorithms. In order to obtain an efficient and robust FXECAP-L algorithm with evolving order, the scaling factor and encoder resolution need to be adjusted manually, which is a time-consuming and costly effort that must be carried out by expert designers. To reduce these costs and efforts, we introduce, for the first time, a strategy for automatic adjustment of the scaling factor and encoder resolution that benefits the rapid development of practical ANC applications. To demonstrate its practical use, we applied the proposed strategy for controlling the noise in an acoustic duct. The practical results demonstrate the automatic adjustment of the FXECAP-L algorithm which maintains high convergence speed at the expense of a small compromise in terms of processing time.

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