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Novel LMS adaptive filtering algorithm with variable step size

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Journal of Measurement Science and Instrumentation 2012年第3期3卷 239-242页

作者：李继明马骥王洋程学珍 College of Information and Electrical Engineering Shandong University of Science and Technology

By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different *** with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.

关键词： adaptive filter variable step size least mean square(LMS)

A new variable step size LMS adaptive algorithm

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A new variable step size LMS adaptive algorithm

variable-step-size second-order-derivative multistep method for solving first-order ordinary differential equations in system simulation

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作者： Qun Niu TianNing Chen School of Mechanical Engineering Xi'an Jiaotong University State Key Laboratory for Strength and Vibration of Mechanical Structures Xi'an Jiaotong University

LMS adaptive filtering algorithm is widely used in adaptive control *** a certain extent the variable step size LMS algorithm can solve the conflict between convergence rate and steady-state *** is difficult for the traditional LMS to solve.A new variable step size LMS adaptive algorithm based on the existing algorithm is proposed in this *** using the gradient of the filter coefficient vector W(n) the algorithm accelerates the convergence speed on the basis of ensuring the convergence *** the same time,the update formula of step size is adjusted to enhance the ability of the algorithm to resist noise ***,the MATLAB simulation results show that the algorithm has faster convergence speed,smaller steady-state error and better robustness.

关键词： LMS Adaptive variable step size Convergence rate Steady-state error

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International Journal of Modeling, Simulation, and Scientific Computing 2020年第1期11卷 42-57页

作者： Lei Zhang Chaofeng Zhang Mengya Liu School of Physics and Electronics Henan University KaifengHenan 475004P.R.China

According to the relationship between truncation error and step size of two implicit second-order-derivative multistep formulas based on Hermite interpolation polynomial,a variable-order and variable-step-size numerical method for solving differential equations is *** stability properties of the formulas are discussed and the stability regions are *** deduced methods are applied to a simulation *** results show that the numerical method can satisfy calculation accuracy,reduce the number of calculation steps and accelerate calculation speed.

关键词： Numerical method variable step size variable order hermite interpolation ordinary differential equations

Dynamic Simulation of Distribution Networks Using Multi-stage Discontinuous Galerkin Method

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 185-196页

作者： Ruizhi Yu Wei Gu Weiqi Liu Peixin Li Wei Liu School of Electrical Engineering Southeast UniversityNanjing 210096China. the School of Electrical Engineering Southeast UniversityNanjing 210096China School of Automation Nanjing University of Science and TechnologyNanjing 210094China

Dynamic simulation plays a fundamental role in security evaluation of distribution networks(DNs).However,the strong stiffness and non-linearity of distributed generation(DG)models in DNs bring about burdensome computation and noteworthy instability on traditional methods which hampers the rapid response of simulation ***,a novel L-stable approximate analytical method with high accuracy is proposed to handle these *** method referred to as multistage discontinuous Galerkin method(MDGM),first derives approximate analytical solutions(AASs)of state variables which are explicit symbolic expressions concerning system ***,in each time window,it substitutes values for symbolic variables and trajectories of state variables are obtained *** paper applies MDGM to DG models to derive ***-truncation-error-based variable step size strategy is also developed to further improve simulation *** addition,this paper establishes detailed MDGM-based dynamic simulation *** case studies on a numerical problem,a modified 33-bus system and a practical large-scale DN,it can be seen that proposed method demonstrates fast and dependable performance compared with the traditional trapezoidal method.

关键词： Approximate analytical method distribution network distributed generation dynamic simulation multi-stage discontinuous Galerkin method variable step size

An Efficient Reference Free Adaptive Learning Process for Speech Enhancement Applications

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Computers, Materials & Continua 2022年第2期70卷 3067-3080页

作者： Girika Jyoshna Md.Zia Ur Rahman L.Koteswararao Deptartment of Electronics and Communication Engineering Koneru Lakshmaiah Education FoundationKL UniversityVaddeswaramGunturAndhra PradeshIndia Department of Electronics and Communication Engineering Koneru Lakshmaiah Education FoundationKL UniversityHyderabadTelanganaIndia

In issues like hearing impairment,speech therapy and hearing aids play a major role in reducing the *** of noise signals from speech signals is a key task in hearing aids as well as in speech *** the transmission of speech signals,several noise components contaminate the actual speech *** paper addresses a new adaptive speech enhancement(ASE)method based on a modified version of singular spectrum analysis(MSSA).The MSSA generates a reference signal for ASE and makes the ASE is free from feeding reference *** MSSA adopts three key steps for generating the reference from the contaminated speech *** are decomposition,grouping and *** generated reference is taken as a reference for variable size adaptive learning *** this work two categories of adaptive learning algorithms are *** are step variable adaptive learning(SVAL)algorithm and time variable step size adaptive learning(TVAL).Further,sign regressor function is applied to adaptive learning algorithms to reduce the computational complexity of the proposed adaptive learning *** performance measures of the proposed schemes are calculated in terms of signal to noise ratio improvement(SNRI),excess mean square error(EMSE)and misadjustment(MSD).For cockpit noise these measures are found to be 29.2850,-27.6060 and 0.0758 dB respectively during the experiments using SVAL *** considering the reduced number of multiplications the sign regressor version of SVAL based ASE method is found to better then the counter parts.

关键词： Adaptive algorithm speech enhancement singular spectrum analysis reference free noise canceller variable step size

GRID-INDEPENDENT CONSTRUCTION OF MULTIstep METHODS

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Journal of Computational Mathematics 2017年第5期35卷 672-692页

作者： Carmen Arevalo Gustaf Soderlind Numerical Analysis Centre for Mathematical Sciences Box 118 SE-22100 Lund Sweden.

A new polynomial formulation of variable step size linear multistep methods is pre- sented, where each k-step method is characterized by a fixed set of k - 1 or k parameters. This construction includes all methods of maximal order （p = k for stiff, and p = k ＋ 1 for nonstiff problems）. Supporting time step adaptivity by construction, the new formulation is not based on extending classical fixed step size methods; instead classical methods are obtained as fixed step size restrictions within a unified framework. The methods are imple- mented in MATLAB, with local error estimation and a wide range of step size controllers. This provides a platform for investigating and comparing different multistep method in realistic operational conditions. Computational experiments show that the new multi- step method construction and implementation compares favorably to existing software, although variable order has not yet been included.

关键词： Linear multistep methods variable step size Adaptive step size step sizecontrol Explicit methods Implicit methods Nonstiff methods Stiff methods Initial valueproblems Ordinary differential equations Differential-algebraic equations Implementa-tion.

Fast Spectrum Estimation in 2-D Direction Finding with MUSIC Algorithm

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Fast Spectrum Estimation in 2-D Direction Finding with MUSIC...