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Optimal Sparsity Tradeoff in l₀-nlms algorithm

IEEE SIGNAL PROCESSING LETTERS 2016年第8期23卷 1121-1125页

作者： Al-Shabili, Abdullah Weruaga, Luis Jimaa, Shihab Khalifa Univ Sci Technol & Res Sharjah U Arab Emirates

The l(0)-normalized least mean squares (l(0)-nlms) is arguably the reference gradient adaptive algorithm for sparse system estimation. However, alike all sparse gradient adaptive algorithms, the l(0)-nlms performance is sensitive to the (adequate) selection of the tradeoff parameter. Highlighted in this letter, the existence of two convergence modes, linked to the negligible and to the significant taps, paves the way for the convergence analysis, which results in a set of nonlinear (quadratic) convergence equations. Therefrom, the minimization of the steady-state misalignment concludes in the optimal tradeoff, which happens to relate to the nlms step size, filter length, plant sparsity, and noise level in an extremely compact fashion. Exhaustive simulation experiments show strong agreement between the analytical predictions and the empirical performance.

关键词： l(0)-norm nlms algorithm sparsity tradeoff

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Research on position tracking control of electro-hydraulic actuator system combining feedforward inverse model controller and exponential functional link network adaptive controller

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2025年第3期239卷 643-658页

作者： Liao, Lianjie Sang, Yong Chen, Tao Jiang, Luming Liu, Jiakuo Dalian Univ Technol State Key Lab High Performance Precis Mfg 2 Linggong Rd Dalian 116023 Peoples R China

The electro-hydraulic actuator system plays a crucial role in indoor high-frequency simulation experiments. Many components of the system exhibit unavoidable nonlinear characteristics, which reduce its dynamic position response capability. Additionally, most algorithms are unsuitable for practical high-frequency conditions due to either local instability or high computational complexity. To improve position tracking accuracy under high-frequency control, a novel combined control strategy is proposed, integrating an appropriate feedforward inverse model controller (FFIMC) with an exponential functional link network adaptive controller (EFLNAC). Initially, the system has reached a stable state under the action of the PID controller. Subsequently, the FFIMC estimates both the model and the inverse model of the PID system by applying the AIC technique developed through the DCT-VSSnlms adaptive algorithm, which extends the system's bandwidth. Following this, the EFLNAC, as the outermost loop, acquires the inverse model of the FFIMC system and updates internal parameters in real-time, thereby enhancing the system's resistance to nonlinear disturbances. Finally, the combined controller is validated through simulations and experiments under various working conditions. The results show a significant increase in the PID system's bandwidth and demonstrate that the tracking error of the signal is maintained within 0.079mm. Therefore, the combined controller proves to be an effective solution for high-precision, high-frequency displacement tracking, offering the advantages of low computational complexity, high accuracy, and strong effectiveness.

关键词： Electro-hydraulic actuator system position control nlms algorithm feedforward inverse model control adaptive control

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Fixed-Point nlms and IPnlms VLSI Architectures for Accurate FECG and FHR Processing

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IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2021年第5期15卷 898-911页

作者： da Costa, Patricia Ucker Paim, Guilherme Giacomini Rocha, Leandro Mateus Cesar da Costa, Eduardo Antonio Melo de Almeida, Sergio Jose Bampi, Sergio Catholic Univ Pelotas UCPel BR-96015560 Pelotas RS Brazil Fed Inst Educ Sci & Technol IFRS BR-99170000 Sertao Brazil Fed Univ Rio Grande Sul UFRGS PGMICRO BR-91509900 Porto Alegre RS Brazil

Capturing signals without noise and interference while monitoring the maternal abdomen's fetal electrocardiogram (FECG) is a challenging task. This method can provide fetal monitoring for long hours, not harming the pregnant woman or the fetus. Such non-invasive FECG raw signal suffers from various interference sources as the bio-electric maternal potentials include her ECG component. Therefore, a critical step in the non-invasive FECG is to design the filtering of components derived from the maternal ECG. There is an increasing demand for portable devices to extract a pure FECG signal and to detect fetal heart rate (FHR) with precision. Dedicated CMOS architectures enable higher energy efficiency in portable devices. This paper proposes VLSI architectures dedicated to FECG extraction and FHR processing. Fixed-point architectures for the FECG detection exploring the nlms (normalized least mean square), IPnlms (improved proportional nlms), and three different division VLSI CMOS architectures are designed herein. An architecture based on the Pan-Tompkins algorithm that processes the FECG for extracting the FHR, extending the functionally of the system, is also proposed. The results show that the nlms and IPnlms based architectures effectively detect the R-peaks of FECG with a detection accuracy of 92.86% and 93.75%, respectively. The synthesis results shows that our nlms architecture proposal saves 13.3 % energy, due to a reduction of 279 clock cycles, compared to the state of the art. On the other hand, the IPnlms algorithm results in +0.89% detection accuracy at the price of 42% additional energy consumption w.r.t nlms.

关键词： Mathematical models Signal to noise ratio Very large scale integration Pregnancy Fetus Fetal heart rate Electrocardiography FECG signal FHR signal hardware architectures nlms algorithm IPnlms algorithm

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A New Method for Searching the Optimal Step Size of nlms algorithm in Intelligent Antennas Arrays Based on Fuzzy Logic and Artificial Neural Networks 34

A New Method for Searching the Optimal Step Size of NLMS alg...

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IEEE Central America and Panama Convention (CONCAPAN XXXIV)

作者： Orozco-Tupacyupanqui, W. Perez-Meana, H. Nakano-Miyatake, M. Inst Politecn Nacl Programa Doctorado Ingn Comunicac & Elect Mexico City DF Mexico Inst Politecn Nacl Escuela Ingn Elect & Mecan Secc Invest & Posgrado Mexico City DF Mexico

ISBN: (纸本)9781479975846

This paper proposes a new approach based on information classification algorithms, fuzzy logic and neural networks for generating the membership functions to be used for searching the optimal step size of the normalized least mean square adaptive algorithm, when it is applied in adaptive linear antenna arrays. To this end a multilayer perceptron neural network, which is trained using the back propagation algorithm and the information obtained from several values estimated from the cost function of nlms algorithm as well as the signal to interference noise ratio, generates the membership functions. Experimental results obtained by computer simulation show that the proposed approach provides fairly good estimation of the membership functions of the fuzzy logic stage used to obtain a near optimal step size. Evaluation results also show the desirable convergence properties of proposed approach when used to optimize adaptive antenna arrays.

关键词： nlms algorithm adaptive linear array membership functions fuzzy logic neural networks

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Analysis of convexly combined recursive inverse algorithms

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International Journal of Information Technology (Singapore) 2022年第5期14卷 2245-2253页

作者： Hilal, Hasan Abu Salman, Mohammad Hameed, Alaa Higher Colleges of Engineering and Technology HCT Dubai United Arab Emirates American University of the Middle East Kuwait Kuwait Department of Computer Engineering Istanbul Sabahattin Zaim University Istanbul Turkey

The RI method, which has only lately been developed, has showed outstanding performance in a wide range of application fields. Convexly linked RI method In this study, we demonstrate the algorithm's tracking evaluation as well as the findings obtained. It is also possible to create a formula for the steady state based on the mean square error (MSE). In this case, it is proposed that a 2-dimensional (2D) form of the technique be used. Comparisons have been made between theoretical and experimental results, and it has been discovered that they are in agreement. Also included in this study are comparisons of this method with that of nlms in both additive white Gaussian noise and additive correlated Gaussian noise settings, both of which are used in a noise canceling situation. According to the results of the simulations, the proposed approach outperforms the nlms algorithm is based on MSE as well as the frequency at which it converges. The 2D form of the approach, on the other hand, exhibited excellent achievement in the images de-noising. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Convex combination nlms algorithm Noise cancelation Tracking analysis

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Enhanced Noise Cancellation: A Variable Step Size Normalized Least Mean Square Approach

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TRAITEMENT DU SIGNAL 2024年第2期41卷 911-918页

作者： Manseur, Abdelghani Dendouga, Abdelhakim Kasdi Merbah Univ Fac New Informat Technol & Commun Dept Elect & Telecommun Ouargla 30000 Algeria Mohamed Khider Univ Fac Sci & Technol Elect Engn Dept Biskra 07000 Algeria Mohamed Khider Univ Identificat Command Control & Commun Lab LI3CUB Biskra 07000 Algeria

Noise cancellation remains a significant challenge in signal processing, particularly when addressing non-stationary and time-varying noise sources. Traditional approaches, such as the Normalized Least Mean Square (nlms) algorithm, are often limited by the fixed step size parameter, which dictates the trade-off between convergence rate and system robustness. In this study, an innovative Variable Step Size nlms (VSS-nlms) algorithm is introduced, designed to dynamically adjust the step size parameter, thereby optimizing performance criteria including precision, robustness, convergence rate, and tracking ability. Employing system identification techniques within an adaptive filtering framework, this research advances the nlms algorithm by incorporating a variable step size parameter that adapts in real-time to the noise environment. The proposed VSS-nlms algorithm is evaluated through extensive simulations, demonstrating a significant enhancement in the balance between Mean Square Error (MSE) reduction and convergence rate over both the conventional nlms and Recursive Least Squares (RLS) algorithms, whilst maintaining computational simplicity. In the context of adaptive filters, the VSS-NLSM algorithm represents a substantial improvement for noise cancellation applications, particularly in scenarios characterized by variable noise dynamics. The results presented herein confirm that the VSS-nlms algorithm not only achieves a superior trade-off between accuracy/robustness and convergence rate/tracking but also sets a new benchmark for adaptive noise cancellation strategies in complex acoustic environments.

关键词： adaptive filtering noise cancellation LMS algorithm nlms algorithm VSS-nlms algorithm variable step size convergence factor Mean Square Error (MSE)

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Feasibility study on the active structural attenuation of multiple band vibrations from two dimensional continuous structures in automotive vehicles

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ADVANCES IN MECHANICAL ENGINEERING 2024年第4期16卷

作者： Hong, Dongwoo Moon, Hojoon Kim, Byeongil Daegu Mechatron & Mat Inst Daegu South Korea Yeungnam Univ Sch Mech Engn Gyongsan 38541 Gyeongsangbuk D South Korea Yeungnam Univ Sch Mech Engn 280 Daehak Ro Gyongsan 38541 Gyeongsangbuk D South Korea

Automotive engine mounts have recently begun using active elements, while prior studies did not account for the actual engine mounting position. The placement and orientation of real automobile engine mounts are considered when modeling, analyzing, and controlling a source structure with an active mounting system. A piezoelectric stack actuator connected in series with an elastomeric mount composes an active mount. When harmonic excitation forces are used, the secondary force required for each active mount is mathematically determined, and the control signal may reduce the vibration by interfering with the input signal. Additionally, the dynamic relationship of the source structure with a variable parameter may be used to reduce horizontal vibrations. Several simulation findings show that these multidirectional (vertical and horizontal) active mounts may minimize excitation vibrations. Additionally, a simulation was performed to reduce vibrations when a complex signal and noise were present. This was achieved by monitoring the system response using the normalized least mean squares (nlms) algorithm, an adaptive filter. The control performance degrades as noisy and complicated signals are generated;however, the mitigation trend is the same according to simulations utilizing adaptive filters.

关键词： Active mount active vibration control automotive engine mount nlms algorithm passive mount piezoelectric stack actuator

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An Efficient nlms-based VLSI Architecture for Robust FECG Extraction and FHR Processing 27

An Efficient NLMS-based VLSI Architecture for Robust FECG Ex...

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27th IEEE International Conference on Electronics, Circuits and Systems (IEEE ICECS)

作者： da Costa, Patricia U. L. Paim, Guilherme Rocha, Leandro da Costa, Eduardo Almeida, Sergio Bampi, Sergio Catholic Univ Pelotas UCPel Grad Program Elect Engn & Comp Pelotas RS Brazil Fed Univ Rio Grande do Sul UFRGS Grad Program Microelect PGMicro Porto Alegre RS Brazil

ISBN: (纸本)9781728160443

This work presents an efficient nlms-based VLSI architecture to extract the fetal electrocardiogram (FECG) and detect the fetal heart rate (FHR), using the adaptive filter strategy. The efficient nlms-based architecture herein investigated can robustly cancel the high-noised mother-related ECG signals, enabling the FHR measurement. We used the Improved Fetal Pan and Tompkins algorithm (IFPTA) to detect fetal R-peak and calculate the FHR. Our nlms-based VLSI architecture effectively detects the R-peaks in the extracted FECG with 93.2% accuracy with the only 2.4 mW of total power dissipation.

关键词： nlms algorithm FHR detetion FECG extration

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A new variable length nlms adaptive algorithm

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DIGITAL SIGNAL PROCESSING 2014年 34卷 82-91页

作者： Mayyas, Khaled AbuSeba, Hani A. Jordan Univ Sci & Technol Dept Elect Engn Irbid 22110 Jordan

The Fractional Tap-length Normalized Least Mean-Square (FT-nlms) adaptive algorithm, a member of the variable tap-length LMS algorithms family, has attracted attention recently due to its robustness and low computational complexity compared with existing variable tap-length algorithms. The parameter Delta in the FT-nlms algorithm controls convergence speed and bias from the optimum tap-length, which necessitates a compromise between them due to its fixed value. Therefore, a well adjusted time-varying Delta(n) can provide both fast convergence speed and small steady state bias. In this paper, a new robust variable Delta(n) FT-nlms is proposed that ensures a large value of Delta(n) when the algorithm is far from the optimum with Delta(n) decreasing as the adaptive filter approaches the optimum even in the presence of uncorrelated noise disturbance. Transient and steady state performance analysis of the proposed algorithm will be presented, where expressions for the algorithm steady state excess Mean-Square Error (MSE), steady state tap-length of the adaptive filter, and steady state E{Delta(infinity)} are derived. Simulation examples are presented in different experimental conditions, which will demonstrate the advantages of the proposed algorithm over existing variable tap-length nlms algorithms. Moreover, simulation results will show that the derived theoretical expressions can predict very well the actual behavior of the proposed algorithm. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Adaptive filtering nlms algorithm Variable length filter Performance analysis

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Stochastic Analysis of the LMS and nlms algorithms for Cyclostationary White Gaussian and Non-Gaussian Inputs

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2018年第18期66卷 4753-4765页

作者： Eweda, Eweda Bershad, Neil J. Bermudez, Jose Carlos M. C4 Adv Solut Abu Dhabi 128627 U Arab Emirates Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92660 USA Univ Fed Santa Catarina Dept Elect Engn BR-88040900 Florianopolis SC Brazil

This paper studies the stochastic behavior of the LMS and nlms algorithms in a system identification framework for a cyclostationary white input without assuming a Gaussian distribution for the input. The input cyclostationary signal is modeled by a white random process with periodically time-varying power. The system parameters vary according to a random-walk. Mathematical models are derived for the mean and mean-square-deviation behavior of the adaptive weights as a function of the input cyclostationarity. Analytical models are first derived for the LMS and nlms algorithms for cyclostationary white inputs. These models show the dependence of the two algorithms upon the kurtosis of the input. Significant differences are found between the behaviors of the two algorithms when the analysis is applied to non-Gaussian cases. Monte Carlo simulations provide strong support for the theory.

关键词： Adaptive filters analysis LMS algorithm nlms algorithm stochastic algorithms non-Gaussian processes

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