检索结果-内蒙古大学图书馆

IEEE Circuits and Systems International Conference on Testing and Diagnosis

作者： Li, Hongbing Tian, Hailin AF Engn Univ Missile Inst Xian Peoples R China

ISBN: (纸本)9781424425860

A new variable-step-size lms algorithm is proposed, and it performance is analyzed. Simulation results indicate that the performance is superior to that of existing VSS algorithm and Nlms algorithm. The proposed algorithm is then applied to adaptive noise jamming cancellation system;the computer simulation shows superior performance over the Nlms algorithm and MVSS algorithm.

关键词： lms algorithm convergence rate Variable-step-size Adaptive filter

来源：评论

学校读者我要写书评

暂无评论

Variable step size lms adaptive filtering based on genetic algorithm

Variable step size LMS adaptive filtering based on genetic a...

引用

International Conference on Information Technology and Management Innovation (ICITMI2012)

作者： Shi Jian Zhang Hua-dong Wu Guo-hui Jiang Xi Hangtian Haihong Test & Control Co Nanchang 330013 Jiangxi Peoples R China Beijing Electromech Inst Beijing 100074 Peoples R China

ISBN: (纸本)9783037855744

A common form of variable step size lms algorithm is presented, which is derived by the extensive analysis about several variable step size lms algorithm. Using genetic algorithm parameter optimization, the algorithm get the optimal value alpha, beta, m and h quickly and efficiently, and not rely on experience or method of trial and error. MATLAB simulation results confirmed the theoretical analysis, the algorithm took on good convergence and tracking properties, and could be widely used in modem digital communication systems.

关键词： Genetic algorithm lms algorithm Convergence Tracking properties digital communication

来源：评论

学校读者我要写书评

暂无评论

A new variable step size lms adaptive filtering algorithm and its simulations

A new variable step size LMS adaptive filtering algorithm an...

引用

International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Wu, Xueli Tan, Zizhong Gao Liang Hebei Univ Sci & Technol Dept Elect Engn Shijiazhuang 050018 Peoples R China

ISBN: (纸本)9783038350125

Aiming at the disadvantage of the variable step size lms adaptive filtering algorithms' convergence speed contradicting its steady-state error, a novel non-liner functional relationship between mu (n) and error signal e(n) was established. On the basis of the functional relationship, a new algorithm of variable step size lms adaptive filtering was presented. The step size factor of the new algorithm is adjusted by the absolute value of the product of the current and former errors. It also uses the absolute estimation error compensation terms' disturbance to speed up the convergence of adaptive filter tap weight vector. At the same time, the algorithm considers the relationship between step length of the last iteration and the former M error signal. As a result the algorithm has higher convergence characteristic and small steady state error. The theoretical analysis and simulation results show that the new algorithm has faster convergence speed, lower steady state error and better performance of noise suppression, also show the overall performance of this algorithm exceeds some others condition.

关键词： variable step-size convergence rate steady-state error lms algorithm

来源：评论

学校读者我要写书评

暂无评论

AN IMPROVERD VARIABLE STEP SIZE lms ADAPTIVE FILTERING algorithm

AN IMPROVERD VARIABLE STEP SIZE LMS ADAPTIVE FILTERING ALGOR...

引用

IEEE Youth Conference on Information, Computing and Telecommunication

作者： Li PingPing Pei TengDa Pei BingNan Hu LiJun Dalian Univ Sch Informat Engn Dalian 116622 Liaoning Prov Peoples R China Jilin Univ Lambton Coll Changchun AH1300012 Peoples R China Marine Chinese Peoples Liberat Army 92819 Dalian AH-116622 Peoples R China

ISBN: (纸本)9781424450756

lms (Least Mean Square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the convergence rate and stead-state misadjustment, which can be overcome through the adjustment of size factor. The paper has analyzed some lms algorithms that already existed and a new improved variable step-size lms algorithm is presented. The computer simulation results are consistent with the theoretic analysis, which show that the algorithm not only has a faster convergence rate, but also has a smaller steady-state error.

关键词： variable step-size lms algorithm convergence rate steady-state error

来源：评论

学校读者我要写书评

暂无评论

A New Variable Step Size lms Adaptive Filtering algorithm and Its Analysis

A New Variable Step Size LMS Adaptive Filtering Algorithm an...

引用

2nd International Conference on Materials and Products Manufacturing Technology (ICMPMT 2012)

作者： Cai Weiju Yangtze Univ Jinzhou Hubei Peoples R China

ISBN: (纸本)9783037855447

The paper proposed a modified lms algorithm of variable step size based on a brief analysis of traditional lms,variable step size lms algorithm and its improved *** novel algorithm based on nonlinear functional relationship between the step-size and the error,increases adaptively at the beginning of the algorithm or when the channel is varying with time,and it would be smaller during the steady *** the algorithm has the excellences of faster constringency,little steady error,tracking the change of the system and avoiding the effects of the noise. The theoretical analysis and computer simulation prove that the algorithm is better than traditional lms algorithm.

关键词： lms algorithm variable step size error signal

来源：评论

学校读者我要写书评

暂无评论

The Data Reuse lms Channel Estimation algorithm in Turbo Equalization

The Data Reuse LMS Channel Estimation Algorithm in Turbo Equ...

引用

5th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Xu, Hua Sun, Gaofei Li, Ming AF Engn Univ Telecommun Engn Inst Xian Shanxi Peoples R China Key Lab Southwest Inst elect&Telecom Tech Chengdu Peoples R China

ISBN: (纸本)9781424436927

The channel estimation is a vital part of Turbo equalization. The structure of combined channel estimation and Turbo equalization iterative update is presented in this paper. The low computation complexity algorithm called soft decision feedback lms algorithm is used in channel estimation and the data-reused method is used in the initial channel estimation to overcome the problem of low convergence rate for lms algorithm. The result of simulation shows that the Turbo equalizer with this channel estimation method not only has good performance but also has ability to tracking the fast varying channel.

关键词： Turbo Equalization Channel estimation lms algorithm Soft decision Data Reused

来源：评论

学校读者我要写书评

暂无评论

FEATURE lms algorithmS

FEATURE LMS ALGORITHMS

引用

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Diniz, Paulo S. R. Yazdanpanah, Hamed Lima, Markus V. S. Univ Fed Rio de Janeiro COPPE UFRJ DEE DELPoli & PEE POB 68504 BR-21941972 Rio De Janeiro RJ Brazil

ISBN: (纸本)9781538646588

In recent years, there is a growing effort in the learning algorithms area to propose new strategies to detect and exploit sparsity in the model parameters. In many situations, the sparsity is hidden in the relations among these coefficients so that some suitable tools are required to reveal the potential sparsity. This work proposes a set of lms-type algorithms, collectively called Feature lms (F-lms) algorithms, setting forth a hidden feature of the unknown parameters, which ultimately would improve convergence speed and steady-state mean-squared error. The key idea is to apply linear transformations, by means of the so-called feature matrices, to reveal the sparsity hidden in the coefficient vector, followed by a sparsity-promoting penalty function to exploit such sparsity. Some F-lms algorithms for lowpass and highpass systems are also introduced by using simple feature matrices that require only trivial operations. Simulation results demonstrate that the proposed F-lms algorithms bring about several performance improvements whenever the hidden sparsity of the parameters is exposed.

关键词： adaptive filtering lms algorithm feature matrix lowpass system highpass system

来源：评论

学校读者我要写书评

暂无评论

Fractional Order lms algorithms: A Review and Application in Signal Denoising 1

引用

19th Chinese Intelligent Systems Conference

作者： Zhang, Haozhe Huo, Hanliang Ma, Ruoxun Mo, Lipo Beijing Technol & Business Univ Sch Math & Stat Beijing 100048 Peoples R China Beijing Technol & Business Univ Res Ctr Consumpt Big Data & Intelligent Decis Mak Beijing 100048 Peoples R China

ISBN: (数字)9789819968473

ISBN: (纸本)9789819968497;9789819968473;9789819968466

Fractional calculus is a powerful mathematical tool for describing memory properties and intermediate processes, integrating it with lms algorithm to fully exploit the historical information in the process of weight adjustment can effectively improve the convergence performance and steady-state performance of lms algorithm. In this paper, we exhaustively review the development of fractional order lms algorithms (FOlmss) in the past decade, discusses their properties, advantages and disadvantages. Then we apply these algorithms to sinusoidal signal denoising, from the perspective of output signal variance to measure the denoising effect of various FOlmss. Finally, we provide some suggestions for the future research direction of FOlms in the hope of its better development.

关键词： Fractional calculus lms algorithm Signal denoising

来源：评论

学校读者我要写书评

暂无评论

Modified lms and Nlms algorithms with a new variable step size

Modified LMS and NLMS algorithms with a new variable step si...

引用

9th International Conference on Control, Automation, Robotics and Vision

作者： Zhao Shengkui Man Zhihong Khoo Suiyang Nanyang Technol Univ Sch Comp Engn Nanyang Ave Singapore 639798 Singapore

ISBN: (纸本)9781424403417

In this paper, the modified lms and Nlms algorithms with variable step-size are presented. It is shown that the variable step size is computed using a ratio of the sums of weighted energy of the output error with two exponential factors alpha and beta, thus the fast error convergence of the modified lms and NIlms algorithms can then be achieved. Also, by properly choosing the values of alpha and beta, the misadjustment can be further improved. A few simulation results are presented in support of the good performance of the proposed algorithms by comparing with other lms-type algorithms.

关键词： lms algorithm Nlms algorithm variable step-size

来源：评论

学校读者我要写书评

暂无评论

A VARIABLE STEP-SIZE (VSS-CC) Nlms algorithm

引用

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1995年第8期E78A卷 1004-1009页

作者： CASCO, F PEREZ, H NAKANO, M LOPEZ, M Universidad Autonoma Metropolitana Mexico City Mexico

A new variable step size Least Mean Square (lms) FIR adaptive filter algorithm (VSS-CC) is proposed. In the VSS-CC algorithm the step size adjustment (alpha) is controlled by using the correlation between the output error (e(n)) and the adaptive filter output ((y) over cap(n)). At small times, e(n) and (y) over cap(n) are correlated which will cause a large a providing faster tracking. When the algorithm converges, the correlation will result in a small size alpha to yield smaller misadjustments. Computer simulations show that the proposed VSS-CC algorithm achieves a better Echo Return Loss Enhancement (ERLE)than a conventional Nlms algorithm. The VSS-CC algorithm was also compared with another variable step algorithm, achieving the VSS-CC a better ERLE when the additive noise is incremented.

关键词： lms algorithm TIME VARYING STEP SIZE VSS-CC lms algorithm ECHO CANCELLATION DOUBLE TALK SINGLE TALK SYSTEM IDENTIFICATION

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：