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14th International Symposium on Electronics and Telecommunications (ISETC)

作者： Dogariu, Laura-Maria Paleologu, Constantin Benesty, Jacob Oprea, Cristina Ciochina, Silviu Univ Politehn Bucuresti Dept Telecommun Bucharest Romania Univ Quebec INRS EMT Montreal PQ Canada

ISBN: (纸本)9781728189215

Solving a high-dimension system identification problem could involve significant challenges in terms of complexity and accuracy of the solution. Due to the large parameter space, a decomposition-based approach fits very well in this context. This was the idea behind the recently developed iterative Wiener filter for multilinear forms, which reformulates the problem using a combination of shorter filters. Nevertheless, there are inherent limitations related to the Wiener solution, while the least-mean-square (lms) adaptive filter would represent a more practical alternative. Consequently, in this paper, we develop lms-based algorithms for multilinear forms, in the context of a multiple-input/single-output system identification problem. Simulation results indicate the good performance of the proposed algorithms, especially in terms of their fast convergence features.

关键词： Adaptive filters lms algorithm Nlms algorithm multilinear forms system identification

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Modified lms algorithms for speech processing with an adaptive noise canceller

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IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING 1998年第4期6卷 338-351页

作者： Greenberg, JE MIT Cambridge MA 02139 USA

A desired signal corrupted by additive noise can often be recovered by an adaptive noise canceller using the least mean squares (lms) algorithm. A major disadvantage of the lms algorithm is its excess mean-squared error, or misadjustment, which increases linearly with the desired signal power. This leads to degrading performance when the desired signal exhibits large power fluctuations and is a serious problem in many speech processing applications. This work considers two modified lms algorithms, the weighted sum and sum methods, designed to solve this problem by reducing the size of the steps in the weight update equation when the desired signal is strong. The weighted sum method is derived;from an optimal method (also developed in this work), which is not generally applicable because it requires quantities unavailable in a practical system. The previously proposed, but ad hoc, sum method is analyzed and compared to the weighted sum method, Analysis of the two modified lms algorithms indicates that either one provides substantial improvements in the presence of strong desired signals and similar performance in the presence of weak desired signals, relative to the unmodified lms algorithm. Computer simulations with both uncorrelated Gaussian noise and speech signals confirm the results of the analysis and demonstrate the effectiveness of the modified algorithms. The modified lms algorithms are particularly suited for signals (such as speech) that exhibit large fluctuations in short-time power levels.

关键词： adaptive filtering adaptive noise cancellation lms algorithm noise reduction

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Dynamic Rate Allocation algorithm Using Adaptive lms End-to-End Distortion Estimation for Video Transmission over Error Prone Network

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2016年第1期20卷 106-110页

作者： Dela Cruz, Angelo R. Vicerra, Ryan Rhay P. Bandala, Argel A. Dadios, Elmer P. De La Salle Univ 2401 Taft Ave Manila 1004 Philippines

Because of the inherent trade-off between source distortion and channel distortion in video transmission systems, joint optimization between bit-rate and distortion is still a challenging task. In this paper, we propose a method where the bit-rate allocation between source and channel encoder is controlled by the estimated end-to-end distortion at the encoder. The distortion estimation scheme is based on the adaptive forward linear predictor using least-mean square (lms) algorithm. The forward predictor used the past values of actual end-to-end distortion to estimate the current distortion. The results show good estimate of end-to-end distortion and the proposed scheme improves video quality as compared to a standard rate control of H.264/AVC. The proposed scheme dynamically allocates the source encoder bits based on the estimated distortion.

关键词： end-to-end distortion bit-rate allocation lms algorithm H.264/AVC

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Stochastic Analysis of the lms and Nlms algorithms for Cyclostationary White Gaussian Inputs

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2014年第9期62卷 2238-2249页

作者： Bershad, Neil J. Eweda, Eweda Bermudez, Jose C. M. Univ Calif Irvine Dept Elect Engn & Comp Sci Newport Beach CA 92660 USA Natl Knowledge Ctr Abu Dhabi U Arab Emirates Univ Fed Santa Catarina Dept Elect Engn BR-88040900 Florianopolis SC Brazil

This paper studies the stochastic behavior of the lms and Nlms algorithms for a system identification framework when the input signal is a cyclostationary white Gaussian process. The input cyclostationary signal is modeled by a white Gaussian random process with periodically time-varying power. Mathematical models are derived for the mean and mean-square-deviation (MSD) behavior of the adaptive weights with the input cyclostationarity. These models are also applied to the non-stationary system with a random walk variation of the optimal weights. Monte Carlo simulations of the two algorithms provide strong support for the theory. Finally, the performance of the two algorithms is compared for a variety of scenarios.

关键词： Adaptive filters analysis lms algorithm Nlms algorithm stochastic algorithms

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Performance Analysis of New Time Varying lms (NTVlms) Adaptive Filtering algorithm in Noise Cancellation System for Speech Enhancement 4

Performance Analysis of New Time Varying LMS (NTVLMS) Adapti...

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4th World Congress on Information and Communication Technologies (WICT)

作者： Siddappaji Sudha, K. L. BMS Coll Engn Bangalore Karnataka India DSCE Bangalore Karnataka India

ISBN: (纸本)9781479981144

This paper compares the performance analysis of our proposed New Time Varying lms (NTVlms) algorithm with other well-known adaptive algorithms such as lms, Nlms, RVSSlms and TVlms algorithm. These algorithms have been tested for their adaptive noise cancellation capabilities in the context of Speech signals corrupted by four variants of noise signals viz White Gaussian noise, Conference noise, Engine noise and Traffic noise. Performance of these algorithms is analyzed based on output SNR. The computer simulation results show that the performance of proposed algorithm is better compared to other algorithms in White Gaussian noise Environment. For the other three noise environments, Nlms algorithm performs well.

关键词： lms algorithm New Time-varying lms algorithm (NTVlms) Normalized lms algorithm (Nlms) Robust Variable step size lms algorithm (RVSSlms) Time-varying lms algorithm (TVlms)

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An Approach to Implement lms and Nlms Adaptive Noise Cancellation algorithm in Frequency domain 5

An Approach to Implement LMS and NLMS Adaptive Noise Cancell...

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5th International Conference on Confluence - The Next Generation Information Technology Summit (Confluence)

作者： Nagal, Rachana Kumar, Pradeep Bansal, Poonam ASET Dept ECE ICE New Delhi India Amity Univ ASET Dept ECE Noida India MSIT Dept CSE Dept New Delhi India

ISBN: (纸本)9781479942367

This paper presents the implementation of adaptive algorithms like Least Mean Square (lms) and Normalized Least Mean Square (Nlms) in the frequency domain and their comparison to that implemented in the time domain. Adaptive filtering using adaptive algorithm in frequency domain can be done by taking Fourier Transform of input signal and independent weigh coefficient. By frequency domain approach significant reduction in mathematical computation has been achieved. An expression for updating the weights is implemented in the frequency domain and statistical analysis has been performed. The SNR (Signal to Noise Ratio) is a parameter used to evaluate the performance with different step size. The signal power and noise power has also been calculated using MATLAB. The SNR of output signal rises about 8-9 times in frequency domain than the time domain.

关键词： lms algorithm Nlms algorithm Time Domain Frequency Domain SNR Signal to Noise Ratio

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New lms Adaptive Filtering algorithm with Variable Step Size

New LMS Adaptive Filtering Algorithm with Variable Step Size

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International Conference on Vision, Image and Signal Processing ICVISP

作者： Zhang Yuan Xi Songtao Nanjing Coll Informat Technol Nanjing Jiangsu Peoples R China Nanjing Res Inst Elect Technol Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538606124

By building a nonlinear function relationship between mu and the error signal e(n), this paper presents a new variable step size lms(Least-Mean-Square)adaptive filtering algorithm, and analyzes the algorithm with various parameters alpha and beta. This step size algorithm avoids the shortage of adjusting step size of SVSlms (variable step size lms based on Sigmoid function). Also in the process of the adaptive steady state it has the virtue of e(n) slightly changing close to zero. Theoretical analysis and computer simulations show that with the proposed algorithm, convergence rate can be improved than the former.

关键词： adaptive filter variable step size adaptive filtering algorithm lms algorithm MSE convergence speed

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Performance analysis of a New Time-Varying lms(NTVlms) Adaptive Filtering algorithm 1

Performance analysis of a New Time-Varying LMS(NTVLMS) Adapt...

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1st International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS)

作者： Siddappaji Sudha, K. L. BMS Coll Engn Bangalore 19 Karnataka India DSCE Bangalore 78 Karnataka India

ISBN: (纸本)9781467367257

A New Time Varying lms (NTVlms) algorithm is proposed and its performance is analysed. The proposed algorithm is applied to adaptive noise cancellation system. The investigations have indicated better performance of the proposed NTVlms algorithm as compared to lms, Nlms, RVSSlms, NVSSlms and TVlms algorithm for stationary signal in terms convergence rate and output SNR except MVSSlms algorithm. For Speech signals proposed NTVlms algorithm is better compared to other algorithms in White Gaussian noise Environment and Nlms algorithm performs well in Conference noise, Engine noise & Traffic noise environments in terms of output SNR.

关键词： lms algorithm New Time-Varying lms algorithm (NTVlms) Time-Varying lms algorithm (TVlms) Variable Step Size lms (VSSlms) algorithm Signal to Noise Ratio (SNR)

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Application of New lms Adaptive Filtering algorithm with Variable Step Size in Adaptive Echo Cancellation 17

Application of New LMS Adaptive Filtering Algorithm with Var...

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IEEE 17th International Conference on Communication Technology (ICCT)

作者： Zhang Yuan Xi Songtao Nanjing Coll Informat Technol Nanjing Jiangsu Peoples R China Nanjing Res Inst Elect Technol Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781509039449

This paper presents a new variable step size lms (Least-Mean-Square) adaptive filtering algorithm in adaptive echo cancellation. This step size algorithm builds a nonlinear function relationship between the step-size parameter and the error signal. Theoretical analysis and computer simulations show that convergence rate can be improved than the former by the proposed algorithm. The new algorithm has good performance. It is applied in the filtering process of adaptive echo cancellation. The filtering effect is good.

关键词： adaptive filter variable step size adaptive filtering algorithm lms algorithm convergence speed adaptive echo canceller

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A New Variable-Step-Size lms Adaptive Filtering algorithm

A New Variable-Step-Size LMS Adaptive Filtering Algorithm

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9th International Conference on Signal Processing

作者： Li, Hongbing Tong, Ningning Liu, Nannan Jiang, Jun AF Engn Univ Missile Inst Xian 713800 Peoples R China Guilin AF Inst Xian 713800 Peoples R China

ISBN: (纸本)9781424421787

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

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