检索结果-内蒙古大学图书馆

International Joint Conference on Neural Networks

作者： Badong Chen Ren Wang Nanning Zheng Jose C. Principe School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an 710049 China

ISBN: (纸本)9781479919611

The mean square convergence of the kernel least mean square (KLMS) algorithm has been studied in a recent paper [B. Chen, S. Zhao, P. Zhu, J. C. Principe, mean square convergence analysis of the kernel least mean square algorithm, Signal Processing, vol. 92, pp. 2624-2632,2012]. In this paper, we continue this study and focus mainly on the initial convergence behavior. Two measures of the convergence performance are considered, namely the weight error power (WEP) and excess mean square error (EMSE). The analytical expressions of the initial decreases of the WEP and EMSE are derived, and several interesting facts about the initial convergence are presented. An illustration example is given to support our observation.

关键词： KLMS mean square convergence weight error power (WEP) excess mean square error (EMSE) least mean square algorithm mean square Converge WEP Seeds Kernel

来源：评论

学校读者我要写书评

暂无评论

Stochastic analysis of the diffusion least mean square and normalized least mean square algorithms for cyclostationary white Gaussian and non-Gaussian inputs

引用

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2021年第12期35卷 2466-2486页

作者： Eweda, Eweda Bershad, Neil J. Bermudez, Jose C. M. Future Univ Dept Elect Engn Cairo Egypt Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA USA Univ Fed Santa Catarina Dept Elect Engn Florianopolis SC Brazil

The diffusion least mean square (DLMS) and the diffusion normalized least mean square (DNLMS) algorithms are analyzed for a network having a fusion center. This structure reduces the dimensionality of the resulting stochastic models while preserving important diffusion properties. The analysis is done in a system identification framework for cyclostationary white nodal inputs. The system parameters vary according to a random walk model. The cyclostationarity is modeled by periodic time variations of the nodal input powers. The analysis holds for all types of nodal input distributions except for distributions with infinite variance. The derived models consist of simple scalar recursions. These recursions facilitate the understanding of the network mean and mean-square dependence upon the 1) nodal weighting coefficients, 2) nodal input kurtosis and cyclostationarities, 3) nodal noise powers, and 4) the unknown system mean-square parameter increments. Optimization of the node weighting coefficients is studied. Also investigated is the stability dependence of the two algorithms upon the nodal input kurtosis and weighting coefficients. Significant differences are found between the behaviors of the DLMS and DNLMS algorithms for non-Gaussian nodal inputs. Simulations provide strong support for the theory.

关键词： adaptive filters least mean square algorithm normalized least mean square algorithm stochastic diffusion algorithms

来源：评论

学校读者我要写书评

暂无评论

On the Impacts of I/Q Imbalance in Analog least mean square Adaptive Filter for Self-Interference Cancellation in Full-Duplex Radios

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第10期71卷 10683-10693页

作者： Le, Anh Tuyen Huang, Xiaojing Tran, Le Chung Guo, Y. Jay Univ Thchnol Sydney Fac Engn & IT Ultimo NSW 2007 Australia Univ Wollongong Fac Engn & Informat Sci Wollongong NSW 2522 Australia

Frequency-dependent in-phase/quadrature-phase imbalance (IQI) is a critical hardware impairment, which affects the performance of the self-interference (SI) cancellation structure in full-duplex systems. A novel frequency-dependent IQI model is proposed in this paper, providing a theoretical tool to evaluate the impacts of this impairment in the analog domain. The model is then applied to investigate the performance of the analog least mean square (ALMS) loop under both frequency-selective and frequency-independent IQI. The degradation in the SI cancellation performance of the ALMS loop is revealed and its upper bound is derived. Numerical results show that the ALMS loop is resilient to both types of IQI with the maximum level of only 3.5 dB performance degradation even when the image rejection ratio is just 15 dB.

关键词： Frequency modulation Radio frequency Interference cancellation Demodulation Frequency-domain analysis Degradation Transceivers In-band Full-duplex analog adaptive filter least mean square algorithm self-interference cancellation I Q imbalance

来源：评论

学校读者我要写书评

暂无评论

Adaptive Modified Versoria Zero Attraction least mean square algorithms

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2020年第12期67卷 3602-3606页

作者： Bhattacharjee, Sankha Subhra Ray, Dwaipayan George, Nithin, V IIT Gandhinagar Dept Elect Engn Gandhinagar 382355 India Qualcomm Bangalore Design Ctr Dept QCT Platform Architecture India Bengaluru 560066 India

Low complexity and ease of implementation provided by zero-attraction-based least mean square (LMS) algorithms have made them popular candidates for sparse system identification. In this brief, a new sparsity aware norm based on a modified Versoria function is proposed, and utilized to develop a novel Versoria zero-attraction LMS (VZA-LMS) algorithm. Moreover, to make the proposed algorithm independent of the zero-attraction parameter, an adaptive zero attractor VZA-LMS (A-VZA-LMS) algorithm is also derived. The bound on learning rate, which ensures convergence in the mean and mean square sense, is derived. Computational complexity of the proposed algorithms are also compared with the existing zero-attraction-based LMS algorithms. Simulation results show that the proposed algorithms provide improved performance over the state-of-the-art algorithms.

关键词： Circuits and systems Convergence Computational complexity Adaptation models Standards Adaptive systems Versoria function sparse system identification least mean square algorithm zero attraction and low complexity

来源：评论

学校读者我要写书评

暂无评论

Robust zero-point attraction least mean square algorithm on near sparse system identification

引用

IET SIGNAL PROCESSING 2013年第3期7卷 210-218页

作者： Jin, Jian Qu, Qing Gu, Yuantao Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

The newly proposed l(1) norm constraint zero-point attraction least mean square algorithm (ZA-LMS) demonstrates excellent performance on exact sparse system identification. However, ZA-LMS has less advantage against standard LMS when the system is near sparse. Thus, in this study, firstly the near sparse system (NSS) modelling by generalised Gaussian distribution is recommended, where the sparsity is defined accordingly. Second, two modifications to the ZA-LMS algorithm have been made. The l(1) norm penalty is replaced by a partial l(1) norm in the cost function, enhancing robustness without increasing the computational complexity. Moreover, the ZA item is weighted by the magnitude of estimation error which adjusts the ZA force dynamically. By combining the two improvements, Dynamic Windowing ZA-LMS (DWZA-LMS) algorithm is further proposed, which shows better performance on NSS identification. In addition, the mean-square performance of DWZA-LMS algorithm is analysed. Finally, computer simulations demonstrate the effectiveness of the proposed algorithm and verify the result of theoretical analysis.

关键词： Cost functions System identification NSS Gaussian distribution Attraction least mean square algorithm zero point

来源：评论

学校读者我要写书评

暂无评论

An acoustic feedback canceler based on probe noise and informative data for hearing aids

引用

SIGNAL IMAGE AND VIDEO PROCESSING 2024年第1期18卷 703-714页

作者： Eren, Yusuf Guvenc, Buket Colak Menguc, Engin Cemal Erciyes Univ Dept Elect & Elect Engn Kayseri Turkiye Kayseri Univ Dept Elect & Elect Engn Kayseri Turkiye

One of the important issues encountered in acoustic feedback canceler (AFC) systems is the bias occurring in the estimation of the acoustic feedback (AF) path. In the literature, a common solution is to inject the probe noise into the loudspeaker to reduce the correlation between the input signal and the loudspeaker signal, that is, to remove the bias occurring in the estimation of the AF path. This approach significantly improves the performance of the AFC systems. However, when considering high filter orders and large-scale input signals, the AFC systems suffer from the data processing cost, and thus their real-time implementations on a chip generally become challenging. To this end, in this paper, we propose an AFC system using jointly probe noise and informative data, named the probe noise-online censoring-least mean square (PN-OC-LMS) based AFC. Thanks to both the OC mechanism and the probe noise injection approach, the proposed PN-OC-LMS-based AFC system not only significantly reduces the data processing cost but also effectively removes the bias effect in the AF path. The mentioned effectiveness of the proposed AFC system is supported by three comprehensive experiments on a real-world AF path measured from a behind-the-ear hearing aid. As a result, in the proposed AFC system, the use of both informative data and the injection of probe noise will enable the design of a long-term working wearable hearing aid that provides low data processing cost and correctly estimates the AF path.

关键词： Acoustic feedback canceler Online censoring strategy least mean square algorithm Adaptive filter Probe noise injection

来源：评论

学校读者我要写书评

暂无评论

Fractional delay Newton structure for Lagrangian interpolation in PV integrated grid connected system

引用

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2024年第3期52卷 1095-1115页

作者： Arora, Ankita Singh, Alka Delhi Technol Univ Dept Elect Engn Delhi 110042 India

This paper proposes a fractional delay (FD) Newton structure for Lagrangian interpolation in single phase grid integrated photovoltaic (PV) system. The structure has been designed for achieving shunt compensation and as a phase locked loop circuit for synchronization. The designed controller performs multiple tasks of feeding the active power to meet the load demand and simultaneously providing reactive power compensation, power factor improvement, and compensating other power quality voltage and load current harmonics. Further, synchronization poses a severe challenge in integrating the PV power electronic converters to the grid. The FD filter is used to discretize the continuous time signal at any time instant using interpolation algorithm employing the non-integral value of the sampling rate delays. The FD delay filter is made adaptive and self-learning by using least mean square algorithm. The designed synchronization technique meets the objective of faithfully tracking the phase of the grid voltage under all grid disturbances such as under voltage, overvoltage, frequency variations, and phase angle disturbances in a precise manner. This paper proposes a fractional delay (FD) Newton structure for Lagrangian interpolation in single phase grid integrated photovoltaic (PV) system. The structure has been designed for achieving shunt compensation and as a phase locked loop circuit for synchronization. The designed controller performs multiple tasks of feeding the active power to meet the load demand and simultaneously providing reactive power compensation, power factor improvement, and compensating other power quality voltage and load current harmonics. Further, synchronization poses a severe challenge in integrating the PV power electronic converters to the grid. The FD filter is used to discretize the continuous time signal at any time instant using interpolation algorithm employing the non-integral value of the sampling rate delays. The FD delay filter is made ada

关键词： adaptive filter least mean square algorithm phase locked loop photovoltaic power quality shunt compensation synchronization

来源：评论

学校读者我要写书评

暂无评论

Advances in Capacitor Health Monitoring Techniques for Power Converters: A Review

引用

IEEE ACCESS 2023年 11卷 133540-133576页

作者： Ramees, M. K. P. Muhammed Ahmad, Md. Waseem Natl Inst Technol Karnataka Mangalore 575025 India

Capacitors play a critical role in power electronic systems, and their health and performance directly impact system reliability and efficiency. This article provides an overview of advanced techniques developed for capacitor monitoring, focusing on diagnosing, estimating, and predicting capacitor health in various power electronic converters. The condition monitoring techniques are categorized based on the type of converter, and a comprehensive review and comparison of various methods are provided within each category. The article covers various techniques, including impedance spectroscopy, frequency response analysis, harmonic analysis, wavelet analysis, short-time Fourier transform, and algorithm-based predictive models. These techniques enable early detection of capacitor faults, accurate estimation of capacitance and equivalent series resistance (ESR), and prediction of the remaining useful life of capacitors. By implementing these advanced monitoring techniques, engineers and researchers can enhance system reliability, prevent unexpected failures, and optimize maintenance and replacement strategies for capacitors in power electronic systems.

关键词： Condition monitoring equivalent series resistance least mean square algorithm support vector machine

来源：评论

学校读者我要写书评

暂无评论

Variable Step-size LMS algorithm Based on Hyperbolic Tangent Function

引用

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第7期42卷 4415-4431页

作者： Li, Long Zhao, Xuesong Harbin Univ Sci & Technol Sch Elect & Elect Engn Harbin 150080 Peoples R China

To solve the problem that the least mean square (LMS) algorithm cannot balance the convergence rate and steady-state mean square error (MSE) well and require excessive manual adjustment of parameters, this paper proposes a parameter-free variable step-size LMS algorithm based on the hyperbolic tangent function. First, the algorithm uses the hyperbolic tangent function to establish a nonlinear relationship between the error and the step size. Based on this, the average value of the error signal is used to update the step size. Further, the accumulated error value is multiplied by its average value and added to the input signal energy. Then, the algorithm is normalized by using this value to prevent the algorithm divergence due to the sudden increase in the signal power. The convergence proof of the proposed algorithm is provided in this paper. The simulation results indicate that the proposed algorithm can automatically adjust the parameters. The convergence rate and the steady-state MSE are better than those of other algorithms for both high and low signal-to-noise ratios.

关键词： least mean square algorithm Hyperbolic tangent function System identification mean square error

来源：评论

学校读者我要写书评

暂无评论

A Comparative Survey of Convex Combination of Adaptive Filters

引用

IETE JOURNAL OF RESEARCH 2023年第2期69卷 940-950页

作者： Vazquez, Angel A. Avalos, J. Gerardo Sanchez, Giovanny Sanchez, Juan C. Perez, Hector Inst Politecn Nacl Mexico City 04260 DF Mexico Inst Politecn Nacl Grad Studies & Res Sect ESIME Culhuacan Mexico City 04260 DF Mexico

Over the last twenty years, combination of adaptive filters has emerged to provide a potential solution in the development of advanced applications, such as channel equalization, active noise control, acoustic echo cancelation, adaptive beamforming, among others. Several authors have demonstrated that the combination of two filters with complementary capabilities improves the overall filter performance in comparison when a single filter is used. Commonly, these combinations employ a fast filter and slow filter to guarantee fast convergence speed and low steady-state mean square error (MSE), respectively, at the cost of increasing their computational complexity. However, those combinations have not been well analysed and compared. Currently, this aspect is crucial since most of the current convex combination of adaptive filters could be implemented in advanced embedded digital devices to be used in real-time signal processing applications. In this work, we evaluate the convex combination of adaptive filters, mainly including those based on least mean square (LMS) algorithm, the affine projection (AP) algorithm and the recursive least mean square (RLS) algorithm. We carry out an extensive performance evaluation to demonstrate the advantages and disadvantages of each approach. Specifically, we simulate them in fixed point, which makes feasible the rapid development of advanced prototypes. This aspect could be potentially valuable to the signal processing engineering communities.

关键词： Adaptive filters Adaptation term Affine projection algorithm Convex combination least mean square algorithm Recursive least mean square algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：