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Proportionate Normalized Least Mean Square algorithms Based on Coefficient Difference

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2010年第5期E93A卷 972-975页

作者： Liu, Ligang Fukumoto, Masahiro Saiki, Sachio Kochi Univ Technol Dept Informat Syst Engn Kami 7828502 Japan

The proportionate normalized least mean square algorithm (PNLMS) greatly improves the convergence of the sparse impulse response. It exploits the shape of the impulse response to decide the proportionate step gain for each coefficient. This is not always suitable. Actually, the proportionate step gain should be determined according to the difference between the current estimate of the coefficient and its optimal value. Based on this idea, an approach is proposed to determine the proportionate step gain. The proposed approach can improve the convergence of proportionate adaptive algorithms after a fast initial period. It even behaves well for the non-sparse impulse response. Simulations verify the effectiveness of the proposed approach.

关键词： adaptive filtering algorithm proportionate adaptation system identification least-mean-squares sparse impulse response

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Variable step-size non-negative normalised least-mean-square-type algorithm

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IET SIGNAL PROCESSING 2015年第8期9卷 618-622页

作者： Jung, Sang Mok Seo, Ji-Hye Park, PooGyeon Pohang Univ Sci & Technol Dept Elect Engn Pohang 790784 Gyungbuk South Korea Pohang Univ Sci & Technol Div Informat Technol Convergence Engn Pohang 790784 Gyungbuk South Korea

This paper proposes a fast and precise adaptive filtering algorithm for online estimation under a non-negativity constraint. A novel variable step-size (VSS) non-negative normalised least-mean-square (NLMS)-type algorithm based on the mean-square deviation (MSD) analysis with a non-negativity constraint is derived. The NLMS-type algorithm under the non-negativity constraint is derived by using the gradient descent of the given cost function and the fixed-point iteration method. Furthermore, the VSS derived by minimising the MSD yields improvement of the filter performance in the aspects of the convergence rate and the steady-state estimation error. Simulation results show that the proposed algorithm outperforms existing algorithms.

关键词： least mean squares methods adaptive filters filtering theory iterative methods variable step-size nonnegative normalised least-mean-square-type algorithm adaptive filtering algorithm online estimation mean-square deviation analysis MSD analysis NLMS-type algorithm cost function fixed-point iteration method steady-state estimation error

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Partial Discharge Location algorithm Based on Total Least-Squares With Matern Kernel in Cable Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第3期19卷 2421-2431页

作者： Lu, Lu Zhou, Kai Zhu, Guangya Yang, Xiaomin Chen, Badong Sichuan Univ Coll Elect & Informat Engn Chengdu 610065 Peoples R China Sichuan Univ High Voltage Lab Coll Elect Engn Chengdu 610065 Peoples R China Jiaotong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China

Partial discharge (PD) location techniques are a useful tool for condition monitoring of electrical apparatus in power systems. However, the noisy PD measurements may significantly degrade the performance of location algorithms. This article deals with the PD location problem by using adaptive filtering techniques. Heretofore, scarce literature focuses on addressing the PD location based on such method. A novel adaptive algorithm, termed as total least-squares (TLS)-Matern kernel (TLS-MK), is proposed. Benefiting from the merits of the Matern kernel, the TLS model can effectively suppress the noise from the direct and reflected waves of the PD source. Meanwhile, the TLS-MK algorithm is used to estimate the time difference, which is used in the PD location. Moreover, the convergence behavior of the TLS-MK algorithm is analyzed. Simulations and experiments show that the proposed algorithm can enhance the location accuracy as compared to state-of-the-art methods for various PD signals.

关键词： Partial discharges Signal processing algorithms Sensors Kernel Estimation Informatics Noise reduction adaptive filtering algorithm location matern kernel partial discharge (PD) total least-squares (TLS)

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Active random noise control using adaptive learning rate neural networks with an immune feedback law

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INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS 2011年第1-2期36卷 29-39页

作者： Sasaki, Minoru Kuribayashi, Takumi Ito, Satoshi Inoue, Yoshihiro Gifu Univ Dept Human & Informat Syst Engn Gifu Japan Gifu Univ Dept Mech & Syst Engn Gifu Japan

In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased in proportion to its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without inducing oscillation. In the proposed method, because an immune feedback law is changing the learning rate of the neural networks individually and adaptively, it is expected that the neural cost function will reach its minimum rapidly, resulting in a reduced training time. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed to validate the convergence properties of the method. Control results show that the adaptive learning rate neural network control structure can outperform linear controllers and conventional neural network controllers for active random noise control.

关键词： Active noise control random noise immune feedback law adaptive filtering algorithm

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Family of affine projection adaptive filters with selective partial updates and selective regressors

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IET SIGNAL PROCESSING 2010年第5期4卷 567-575页

作者： Abadi, M. S. E. Mehrdad, V. Shahid Rajaee Teacher Training Univ Fac Elect & Comp Engn Tehran Iran

In this study the concepts of selective partial updates (SPU) and selective regressors (SR) in the affine projection adaptive filtering algorithm are combined and the family of affine projection algorithms (APAs) with SPU and SR features are established. These algorithms are computationally efficient. The mean-square performance of the presented algorithms are analysed based on the energy conservation arguments of Sayed's group. This analysis does not need to assume a Gaussian or white distribution for the regressors. The authors demonstrate the performance of the presented algorithms through simulations. The good agreement between theoretically predicted and actually observed performances is also demonstrated.

关键词： Integral transforms selective regressors filtering methods in signal processing SR adaptive filtering algorithm adaptive filters regression analysis energy conservation SPU mean-square performance selective partial updates mean square error methods affine projection algorithms affine transforms Other topics in statistics

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A Novel Widely-Linear Complex-Valued Diffusion VSS-LMS algorithm for Distributed Network and Its Performance Analysis

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2024年第10期43卷 6689-6710页

作者： Long, Xiaoqiang Zhao, Haiquan Hou, Xinyan Quan, Wei Southwest Jiaotong Univ Sch Elect Engn Chengdu 610031 Peoples R China Minist Educ Key Lab Magnet Suspens Technol & Maglev Vehicle Chengdu 610031 Peoples R China

To address the shortcomings of the widely-linear complex-valued distributed adaptive filtering algorithm that cannot combine convergence speed and steady-state performance when using a fixed step-size strategy. In this paper, by making the partial derivative of the square of the sum of a priori error and a posteriori error with respect to step-size equal to zero, we propose a novel variable step-size (VSS) strategy, which is formulated as a function of a priori error and a posteriori error. In addition, a corresponding adaptive filtering algorithm is proposed by using the VSS strategy. Then in the process of parameter update, the moving average method is used to avoid large perturbations in iteration of the algorithm. Secondly, the theoretically analysis of the transient and steady-state performance of the proposed algorithm is provided. Finally, in the numerical simulation experiments, the effect of each parameter on the algorithm is tested, the result of the comparison with the fixed-step algorithm illustrates that the proposed algorithm has more superiority, and the high degree of matching between theory and experiment also verifies the feasibility and accuracy of the theoretical analysis method.

关键词： A priori error A posteriori error Variable step-size strategy adaptive filtering algorithm

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Partial Discharge Signal Denoising with Recursive Continuous S-Shaped algorithm in Cables

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IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION 2021年第5期28卷 1802-1809页

作者： Lu, Lu Zhou, Kai Zhu, Guangya Chen, Badong Yang, Xiaomin Sichuan Univ Coll Elect & Informat Engn Chengdu Peoples R China Sichuan Univ Coll Elect Engn High Voltage Lab Chengdu Peoples R China Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian Peoples R China

Partial discharge (PD) detection plays a vital role in on-line condition monitoring of electrical apparatus in the power systems. However, the noise of PD measurements significantly degrades the performance of detection algorithms. In this paper, we focus on developing an adaptive filtering technique for the PD denoising problem. Heretofore, there are just a few literature reviews addressing the PD denoising based on such a method. The proposed recursive continuous S-shaped (RCSS) algorithm integrates the advantages of recursive strategy and continuous S-shaped function into adaptive noise cancellation (ANC) system, yielding enhanced filtering performance. The proposed algorithm can tackle PD noises in both Gaussian and impulsive scenarios, which is easy to implement in practical applications. The convergence behavior is also analyzed. Extensive simulation and experimental results confirm that the proposed algorithm can address polluted PD pulses, even in excessively noisy conditions, resulting in smaller mean square error (MSE) as compared to other state-of-the-art algorithms.

关键词： Partial discharges Partial discharge measurement filtering Noise reduction Stability analysis Pollution measurement Power system reliability partial discharge (PD) PD denoising adaptive filtering algorithm recursive strategy cables

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Subspace-Based adaptive Method for Estimating Direction-of-Arrival With Luenberger Observer

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第1期59卷 145-159页

作者： Xin, Jingmin Zheng, Nanning Sano, Akira Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China Keio Univ Dept Syst Design Engn Yokohama Kanagawa 2238522 Japan

In this paper, we propose a computationally simple and efficient subspace-based adaptive method for estimating directions-of-arrival (AMEND) for multiple coherent narrowband signals impinging on a uniform linear array (ULA), where the previously proposed QR-based method is modified for the number determination, a new recursive least-squares (RLS) algorithm is proposed for null space updating, and a dynamic model and the Luenberger state observer are employed to solve the estimate association of directions automatically. The statistical performance of the RLS algorithm in stationary environment is analyzed in the mean and mean-squares senses, and the mean-square-error (MSE) and mean-square derivation (MSD) learning curves are derived explicitly. Furthermore, an analytical study of the RLS algorithm is carried out to quantitatively compare the performance between the RLS and least-mean-square (LMS) algorithms in the steady-state. The theoretical analyses and effectiveness of the proposed RLS algorithm are substantiated through numerical examples.

关键词： adaptive filtering algorithm direction-of-arrival (DOA) estimation learning curve Luenberger observer state estimation transient analysis

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An Improved FXLMS algorithm Based on Error Weight for Active Vibration Control of Plates

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JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES 2024年第3期12卷 3289-3303页

作者： Wu, Tao Chen, Tong Yan, Hui Qu, Jianjun Harbin Inst Technol Sch Mechatron Engn Harbin Peoples R China Univ Michigan Coll Engn Ann Arbor MI USA

PurposeThis paper aims to address the limitations of the filtered-x least mean square (FXLMS) control algorithm in terms of significant noise in filtered results and hindered convergence and steady-state error reduction due to fixed-step size *** this study, a new adaptive filtering algorithm based on error weight is proposed. Multiple moment weight errors are introduced into the objective function, and the error weights are automatically calculated during the iterative process. The step size is optimized to accelerate convergence speed and curtail steady-state error. The state space equation and transfer function expression of the simply supported plate system are calculated, and a hybrid control algorithm for plate vibration control is *** proposed algorithm is simulated and compared with various existing variable step size algorithms and gradient-based least-squares (GLS) algorithms using Mathematica software. The simulation results demonstrate that the proposed algorithm achieves a convergence rate at least six iteration steps ahead of other algorithms, with a minimum reduction of 0.00405 in the average absolute error. This indicates the superiority of the proposed algorithm in terms of convergence speed and steady-state error *** proposed algorithm demonstrates clear advantages in enhancing the rate of convergence of the FXLMS control algorithm and reducing steady-state error. Future research can focus on reducing variable step input parameters and minimizing algorithmic computational complexity.

关键词： adaptive filtering algorithm Error weight FXLMS algorithm Vibration suppression Hybrid control algorithm

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A novel mobile real time monitoring system for heart rate 13

A novel mobile real time monitoring system for heart rate

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13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Hu, Haiyan Yuan, Zelong Wang, Jin Zhao, Jiahui Jilin Business & Technol Coll Dept Informat Engn Changchun 130507 Peoples R China

ISBN: (纸本)9781665438926

In order to effectively improve the performance of heart rate real-time detection, a novel heart rate mobile real-time monitoring system is designed. The paper states the whole scheme of the system and the detailed design of each model. First, the pulse sensor is used to detect heart rate, and then, the adaptive filtering algorithm is used to process the collected signal to make the heart rate data more accurate. Experimental results verify the effectiveness of the method.

关键词： Heart rate Real time monitoring adaptive filtering algorithm

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