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Acceleration harmonic identification for an electro-hydraulic servo shaking table based on the normalized least-mean-square adaptive algorithm

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JOURNAL OF VIBRATION AND CONTROL 2013年第1期19卷 47-55页

作者： Yao Jianjun Jiang Guilin Di Duotao Liu Sheng Harbin Engn Univ Coll Mech & Elect Engn Harbin 150001 Peoples R China Harbin Engn Univ Coll Automat Harbin 150001 Peoples R China

For an electro-hydraulic servo shaking table, there are nonlinearities, which cause acceleration harmonic distortion when they corresponds to a sine acceleration excitation signal. The work here is to develop an acceleration harmonic identification algorithm by using the normalized least-mean-square (LMS) adaptive algorithm, whose weights are updated by the error between the acceleration response and the estimated acceleration signal. The input vector is generated by the reference harmonics and the 90a phase shift. When the identification algorithm converges, the amplitude and phase of each harmonic can be computed from the weight vector. Experimental results show that the proposed harmonic identification has good real-time performance and a fast convergence rate, and it can identify harmonics on-line with high precision both in amplitude and in phase.

关键词： Acceleration distortion amplitude and phase electro-hydraulic servo shaking table harmonic identification normalized least-mean-square algorithm

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normalized least-mean-square algorithmS WITH MINIMAX CONCAVE PENALTY

NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE...

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

作者： Kaneko, Hiroyuki Yukawa, Masahiro Keio Univ Dept Elect & Elect Engn Tokyo Japan RIKEN Ctr Adv Intelligence Project Wako Saitama Japan

ISBN: (纸本)9781509066315

We propose a novel problem formulation for sparsity-aware adaptive filtering based on the nonconvex minimax concave (MC) penalty, aiming to obtain a sparse solution with small estimation bias. We present two algorithms: the first algorithm uses a single firm-shrinkage operation, while the second one uses double soft-shrinkage operations. The twin soft-shrinkage operations compensate each other, promoting sparsity while avoiding a serious increase of biases. The whole cost function is convex in certain parameter settings, while the instantaneous cost function is always nonconvex. Numerical examples show the superiority compared to the existing sparsity-aware adaptive filtering algorithms in system mismatch and sparseness of the solution.

关键词： adaptive filtering normalized least-mean-square algorithm minimax concave penalty proximal forward-backward splitting soft/firm shrinkage

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A variable-step-size NLMS algorithm using statistics of channel response

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SIGNAL PROCESSING 2010年第6期90卷 2107-2111页

作者： Shi, Kun Ma, Xiaoli Texas Instruments Inc DSP Solut R&D Ctr Dallas TX 75243 USA Georgia Inst Technol Sch ECE Atlanta GA 30332 USA

This paper proposes a new variable-step-size control for the normalized least-mean-square (NLMS) algorithm. A step-size vector is used, with a different value for each adaptive weight. With prior knowledge of the channel impulse response statistics, the optimal step-size vector is obtained by minimizing the mean-square deviation (MSD) between the optimal and estimated filter coefficients. In addition, filter convergence is proved and the relationship between the proposed and existing algorithms are analyzed. The proposed method achieves better steady-state performance compared to existing algorithms. The effectiveness of the proposed algorithm is demonstrated through computer simulations. Published by Elsevier B.V.

关键词： normalized least-mean-square algorithm Variable step size Adaptive filters Channel response statistics

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Adaptive filtering algorithms with selective partial updates

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2001年第8期48卷 762-769页

作者： Dogançay, K Tanrikulu, O Univ S Australia Sch Elect & Informat Engn Mawson Lakes SA 5095 Australia Tellabs Media Proc Technol Bedford MA 01730 USA

In some applications of adaptive filtering such as active noise reduction, and network and acoustic echo cancellation, the adaptive filter may be required to have a large number of coefficients in order to model the unknown physical medium with sufficient accuracy. The computational complexity of adaptation algorithms is proportional to the number of filter coefficients. This implies that, for long adaptive filters, the adaptation task can become prohibitively expensive, ruling out cost-effective implementation on digital signal processors. The purpose of partial coefficient updates is to reduce the computational complexity of an adaptive filter by adapting a block of the filter coefficients rather than the entire filter at every iteration. In this paper, we develop a selective-partial-update normalized least-mean-square (NI,MS) algorithm, and analyze its stability using the traditional independence assumptions and error-energy bounds. Selective partial updating is also extended to the affine projection (AP) algorithm by introducing multiple constraints. The new algorithms appear to have good convergence performance as attested to by computer simulations with real speech signals.

关键词： acoustic echo cancellation adaptive filters affine projection algorithm normalized least-mean-square algorithm partial updating

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Close-Form Expression of One-Tap normalized LMS Carrier Phase Recovery in Optical Communication Systems 4

Close-Form Expression of One-Tap Normalized LMS Carrier Phas...

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4th International Conference on Wireless and Optical Communications (IWOC)

作者： Xu, Tianhua Jacobsen, Gunnar Popov, Sergei Li, Jie Liu, Tiegen Zhang, Yimo UCL London WC1E 7JE England Royal Inst Technol SE-16440 Stockholm Sweden Acreo Swedish ICT AB SE-16440 Stockholm Sweden Tianjin Univ Tianjin 300072 Peoples R China

ISBN: (纸本)9781510601550

The performance of long-haul high speed coherent optical fiber communication systems is significantly degraded by the laser phase noise and the equalization enhanced phase noise (EEPN). In this paper, the analysis of the one-tap normalized least-mean-square (LMS) carrier phase recovery (CPR) is carried out and the close-form expression is investigated for quadrature phase shift keying (QPSK) coherent optical fiber communication systems, in compensating both laser phase noise and equalization enhanced phase noise. Numerical simulations have also been implemented to verify the theoretical analysis. It is found that the one-tap normalized least-mean-square algorithm gives the same analytical expression for predicting CPR bit-error-rate (BER) floors as the traditional differential carrier phase recovery, when both the laser phase noise and the equalization enhanced phase noise are taken into account.

关键词： Coherent optical detection optical fiber communication carrier phase recovery normalized least-mean-square algorithm laser phase noise equalization enhanced phase noise

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Adaptive noise reduction for Fiber Optic Gyroscopes in borehole applications

Adaptive noise reduction for Fiber Optic Gyroscopes in boreh...

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6th International Symposium on Instrumentation and Control Technology

作者： Yan Tingyang Zhang Chunxi Gao Shuang Ma Zongfeng Beijing Univ Aeronaut & Astronaut Sch Instrumentat Sci & Optoelect Engn Beijing 100083 Peoples R China

ISBN: (纸本)081946452X

Fiber Optic Gyroscopes (FOGS) have been investigated and proposed as alternative sensors to magnetometers in borehole surveying applications due to their compactness, ruggedness, low cost and high environmental insensitivity. However, FOGs are subject to high measurement noise from various sources, which deteriorates the performance and quality of FOGS, thus the overall system accuracy is limited. To improve the accuracy of the surveying system, adaptive filtering techniques are utilized to reduce the noise level at the output of the FOG. A Forward Linear Prediction (FLP) filter based on normalized least-mean-square (NLMS) adaptive algorithm was designed and evaluated using kinematic data. Results show that the FLP filter can suppress the FOG noise to a certain degree and a satisfactory signal-to-noise ratio improvement can be achieved using this method.

关键词： fiber optic gyroscope noise reduction forward linear prediction normalized least-mean-square algorithm

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Adaptive prediction of time-varying channels for coded OFDM systems

Adaptive prediction of time-varying channels for coded OFDM ...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Schafhuber, D Matz, G Hlawatsch, F Vienna Univ Technol Inst Commun & Radio Frequency Engn A-1040 Vienna Austria

ISBN: (纸本)0780374029

We propose adaptive channel predictors for orthogonal frequency division multiplexing (OFDM) communications over time-varying channels. Successful application of the normalized least-mean-square (NLMS) and recursive least-squares (RLS) algorithms is demonstrated. We also consider the use of adaptive channel predictors for delay-free equalization, thereby avoiding the need for regular transmission of pilot symbols. Simulation results demonstrate the good performance of the proposed techniques.

关键词： adaptive estimation time-varying channels OFDM modulation prediction theory least mean squares methods recursive estimation adaptive equalisers adaptive prediction time-varying channels coded OFDM systems adaptive channel predictors orthogonal frequency division multiplexing OFDM communications normalized least-mean-square algorithm NLMS algorithm recursive least-squares algorithm RLS algorithm delay-free equalization performance

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DELAYLESS SOFT-DECISION DECODING OF HIGH-QUALITY AUDIO TRANSMITTED OVER AWGN CHANNELS

DELAYLESS SOFT-DECISION DECODING OF HIGH-QUALITY AUDIO TRANS...

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

作者： Pflug, Florian Fingscheidt, Tim Tech Univ Carolo Wilhelmina Braunschweig Inst Commun Technol D-38106 Braunschweig Germany

ISBN: (纸本)9781457705397

Short-range wireless audio transmission with high quality on the one hand often encounters error-prone channels, while on the other hand decoding delay plays a critical role in the application. A lot of prior art in audio error concealment is either only intuitively motivated or adds too much delay to the transmission. In this paper we propose a framework for transmitted audio error concealment without any algorithmic delay. As a novelty, it strongly follows a Bayesian approach for quantized but uncompressed audio, which can in principle be applied to any type of wireless channel yielding some kind of reliability information. Two methods to compute audio prediction coefficients are presented, one based on the autocorrelation method, the other one on the normalized least-mean-square (NLMS) algorithm. Simulation results for additive white Gaussian noise (AWGN) channels show the significant effect of the proposed approaches.

关键词： delayless soft-decision audio decoding linear prediction normalized least-mean-square algorithm autocorrelation Levinson-Durbin algorithm

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DELAYLESS SOFT-DECISION DECODING OF HIGH-QUALITY AUDIO TRANSMITTED OVER AWGN CHANNELS

DELAYLESS SOFT-DECISION DECODING OF HIGH-QUALITY AUDIO TRANS...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Florian Pflug Tim Fingscheidt Institute for Communications Technology Technische Universitat Braunschweig Schleinitzstr. 22 D-38106 Braunschweig Germany

ISBN: (纸本)9781457705380

关键词： delayless soft-decision audio decoding linear prediction normalized least-mean-square algorithm autocorrelation Levinson-Durbin algorithm

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An Improved Adaptive Channel Estimation Method for Multiuser Multiantenna OFDM Systems

An Improved Adaptive Channel Estimation Method for Multiuser...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Yue-Xing Gao Jie Yang Qing-Min Meng Wei-Ping Zhu Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications N Institute of Signal Processing and TransmissionNanjing University of Posts and TelecommunicationsNan Institute of Signal Processing and TransmissionNanjing University of Posts and TelecommunicationsNan

An improved normalized least-mean squares (NLMS) channel estimation method using a time-varying convergence factor is proposed for multiuser and multiantenna systems. The new method does not need to estimate the scalar ambiguity matrix, and is guaranteed to be convergent to the Wiener solution in the mean square sense. Comparing with the basic NLMS algorithm, the improved method has a faster convergence speed with a slightly higher computational complexity only. Computer simulations show that the improved method also has a good performance in tracking the channel responses.

关键词： Multiuser and multiantenna Adaptive algorithms normalized least-mean-square algorithm Convergence speed Computational complexity

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