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Direct frequency estimation based adaptive algorithm for a second-order adaptive FIR notch filter

SIGNAL PROCESSING 2008年第2期88卷 315-325页

作者： Punchalard, R. Lorsawatsiri, A. Loetwassana, W. Koseeyaporn, J. Wardkein, P. Roeksabutr, A. Mahanakorn Univ Technol Dept Telecommun Engn Bangkok 10530 Thailand King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Telecommun Engn Bangkok 10520 Thailand

This work deals with the problem of the frequency estimation of a sinusoidal signal corrupted by broad-band noise. The direct frequency estimation based adaptive algorithm for a second-order adaptive finite impulse response (FIR) notch filter (AFNF) is thus proposed. The proposed algorithm employs the bias removal technique to remove the bias existing in the estimated parameter. The performances including the rate of convergence and the mean square error (MSE) can be easily controlled by using only one parameter, i.e., step size parameter. Moreover, the proposed filter is simple to implement and suitable for real-time applications. In addition, the difference equations for the convergence in the mean and mean square, and the closed form expressions for the steady-state estimation bias and MSE are also carried out. Finally, the simulation results are provided to confirm the theoretical analysis. (c) 2007 Elsevier B.V. All rights reserved.

关键词： FIR notch filter gradient algorithm unbiased

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On the parameterization of Hermite transform with application to the compression of QRS complexes

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SIGNAL PROCESSING 2017年第0期131卷 113-119页

作者： Brajovic, Milos Orovic, Irena Dakovic, Milos Stankovic, Srdjan Univ Montenegro Dept Elect Engn Podgorica 20000 Montenegro

The concentration and sparsity of signal representation in the Hermite transform (HT) basis may highly depend on a properly chosen scaling factor and discrete time shift parameter. In that sense, we propose a simple and efficient iterative procedure for automatic determination of the optimal scaling factor. The optimization criterion is based on the l(1)-norm acting as a measure of signal concentration in the HT domain. Instead of centering the signal at the zero time instant, we also propose to shift the center for a few points left or right, which will additionally improve the concentration. An important application of the proposed optimization approach is the compression of QRS complexes, where properly chosen scaling factor and time-shift increase the compression performance. The results are verified using synthetic and real examples and compared with the existing approach for the compression of QRS complexes. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Concentration measures gradient algorithm ECG signal Hermite function Hermite transform QRS complex

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Minimum-Time Selective Control of Homonuclear Spins

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2015年第5期23卷 2018-2025页

作者： Zhang, Tian-Ming Wu, Re-Bing Zhang, Fei-Hao Tarn, Tzyh-Jong Long, Gui-Lu Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Ctr Quantum Informat Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Dept Phys Collaborat Innovat Ctr Quantum Matter Beijing 100084 Peoples R China Washington Univ Dept Elect & Syst Engn St Louis MO 63130 USA

In nuclear magnetic resonance (NMR) quantum computation, the selective control of multiple homonuclear spins is usually slow because their resonance frequencies are very close to each other. To quickly implement the controls against decoherence effects, this brief presents an efficient numerical algorithm for designing minimum-time local transformations in two homonuclear spins. We obtain an accurate minimum-time estimation via geometric analysis on the two-timescale decomposition of the dynamics. Such estimation narrows down the range of search for the minimum-time control with a gradient-type optimization algorithm. Numerical simulations show that this method can remarkably reduce the search efforts, especially when the frequency difference is very small and the control field is high. Its effectiveness is further demonstrated by NMR experiments with two homunuclear carbon spins in a trichloroethylene (C2H1Cl3) sample system.

关键词： Geodesic trajectory gradient algorithm quantum control time optimal control time-scale decomposition

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Drag Minimization for Navier-Stokes Flow

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NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS 2009年第5期25卷 1149-1166页

作者： Gao, Zhiming Ma, Yichen Zhuang, Hongwei Inst Appl Phys & Computat Math LCP Beijing 100088 Peoples R China Xi An Jiao Tong Univ Sch Sci Xian 710049 Shaanxi Peoples R China Engn Coll Armed Police Force Sian 710086 Shaanxi Peoples R China

This paper investigates the drag minimization in a two-dimensional flow which is governed by a nonhomogeneous Navier-Stokes equations. Two approaches are utilized to derive shape gradient of the cost functional. The first one is to use the shape derivative of the fluid state and its associated adjoint state;the second one is to utilize the differentiability of a minimax formulation involving a Lagrange functional with a function space parametrization technique. Finally, a gradient type algorithm is effectively formulated and implemented for the mentioned drag minimization problem. (C) 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 25: 1149-1166, 2009

关键词： gradient algorithm minimax principle Navier-Stokes equations shape derivative shape optimization

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Recursive Parameter Estimation algorithms and Convergence for a Class of Nonlinear Systems with Colored Noise

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2016年第10期35卷 3461-3481页

作者： Wang, Yanjiao Ding, Feng Jiangnan Univ Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China

Parameter estimation is important for controller design of linear systems and nonlinear systems. The parameters of the systems can be estimated through some identification algorithms. This paper presents a recursive generalized extended least squares algorithm and a generalized extended stochastic gradient (GESG) algorithm for identifying the parameters of a class of nonlinear systems. Furthermore, a multi-innovation GESG algorithm is derived to improve the estimation accuracy. The simulation example is provided to test the effectiveness of the proposed algorithms.

关键词： Recursive identification Least squares gradient algorithm Performance analysis Nonlinear system

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A new stabilized finite element method for shape optimization in the steady Navier-Stokes flow

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APPLIED NUMERICAL MATHEMATICS 2010年第8期60卷 816-832页

作者： Gao, Zhiming Ma, Yichen Inst Appl Phys & Computat Math Lab Computat Phys Beijing 100088 Peoples R China Xi An Jiao Tong Univ Sch Sci Xian 710049 Shaanxi Peoples R China

This paper investigates shape optimization of a solid body located in Navier-Stokes flow in two dimensions. The minimization problem of total dissipated energy is established in the fluid domain. The discretization of Navier-Stokes equations is accomplished using a new stabilized finite element method which does not need a stabilization parameter or calculation of high order derivatives. We derive the structures of discrete Eulerian derivative of the cost functional by a discrete adjoint method with a function space parametrization technique. A gradient type optimization algorithm with a mesh adaptation technique and a mesh moving strategy is effectively formulated and implemented. (C) 2010 Published by Elsevier B.V. on behalf of IMACS.

关键词： Discrete adjoint method Shape optimization Stabilized finite element method gradient algorithm Navier-Stokes equations

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A Study on Adaptive Notch Filter Using Exponential All-Pass Transfer Function

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ELECTRONICS AND COMMUNICATIONS IN JAPAN 2010年第5期93卷 8-14页

作者： Kobayashi, Masaki Wang, Chi Chubu Univ Kasugai Aichi 487 Japan

We propose an adaptive notch filter that realizes the phase shift of the all-pass filter by the expression of Fourier sine series. The method of controlling the weights of the all-pass filter formed by IIR filters is well known. However, these adaptive notch filters have not been put to practical use due to the peculiar stability problems of IIR filters and the problem of determining the degree of the IIR filter. The proposed adaptive notch filter is always stable since the all-pass filter is formed by exponential filters. Furthermore, the adaptive algorithm is a simple gradient-based algorithm and convergence of weights is guaranteed. The degree of the all-pass filter depends only on the required steepness of the elimination characteristic and does not depend on the number of narrowband signals that are to be eliminated. Furthermore, the proposed method is suitable for practical use because the elimination characteristic is hardly influenced by a broadband signal added to the narrowband signal. The analytical results and a rigorous verification of the above features by computer simulation are presented. (C) 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(5): 8-14, 2010;Published online in Wiley Inter Science (***). DOI 10.1002/ecj.10256

关键词： phase shift exponential filter all-pass filter gradient algorithm estimation

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Shape Optimization of a Body in the Oseen Flow

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NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS 2010年第6期26卷 1642-1659页

作者： Wang, Axia Ma, Yichen Gao, Zhiming Xi An Jiao Tong Univ Sch Sci Xian 710049 Shaanxi Peoples R China Changan Univ Sch Sci Xian 710064 Shaanxi Peoples R China Inst Appl Phys & Computat Math Beijing 100088 Peoples R China

This article is concerned with a numerical simulation of shape optimization of the Oseen flow around a solid body. The shape gradient for shape optimization problem in a viscous incompressible flow is computed by the velocity method. The flow is governed by the Oseen equations with mixed boundary conditions containing the pressure. The structure of continuous shape gradient of the cost functional is derived by using the differentiability of a minimax formulation involving a Lagrange functional with a function space parametrization technique. A gradient type algorithm is applied to the shape optimization problem. Numerical examples show that our theory is useful for practical purpose and the proposed algorithm is feasible. (C) 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 26: 1642-1659, 2010

关键词： gradient algorithm minimax formulation shape optimization the Oseen equations

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Adaptive unit-vector law with time-varying gain for finite-time parameter estimation in LTI systems

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APPLIED NUMERICAL MATHEMATICS 2020年 155卷 16-28页

作者： Kapetina, M. N. Pisano, A. Rapaic, M. R. Usai, E. Univ Novi Sad Fac Tech Sci Dept Comp & Control Engn Trg Dositeja Obradovica 6 Novi Sad 21000 Serbia Univ Cagliari Dept Elect & Elect Engn Via Marengo I-09123 Cagliari Italy

A continuation of previous authors' work on adaptive parameter estimation for linear dynamical systems having irrational transfer function is presented in this work. An original modification of the gradient algorithm, inspired by the variable structure control techniques and additionally featuring a time-varying adaptation gain, is presented and analyzed using Lyapunov techniques. The exposition is illustrated by several numerical examples which illustrate the effectiveness of the proposed algorithm. (C) 2019 Published by Elsevier B.V. on behalf of IMACS.

关键词： Adaptive parameter estimation Fractional order systems Distributed parameter systems Delayed systems gradient algorithm Lyapunov stability

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Extreme Learning Machine Under Minimum Information Divergence Criterion

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IEEE ACCESS 2020年 8卷 122026-122035页

作者： Song, Chengtian Pan, Lizhi Liu, Qiang Jiang, Zhihong Jia, Jianguang Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Ordnance Sci Inst China Beijing 100089 Peoples R China PLA AMS Inst Syst Engn Beijing 100091 Peoples R China

In recent years, extreme learning machine (ELM) and its improved algorithms have been successfully applied to various classification and regression tasks. In these algorithms, MSE criterion is commonly used to control training error. However, MSE criterion is not suitable to deal with outliers, which can exist in general regression or classification tasks. In this paper, a novel extreme learning machine under minimum information divergence criterion (ELM-MinID) is proposed to deal with the training set with noises. In minimum information divergence criterion, the Gaussian kernel function and Euclidean information divergence are utilized to substitute the mean square error (MSE) criterion to enhance the anti-noise ability of ELM. Experimental results on two synthetic datasets and eleven benchmark datasets show that this method is superior to traditional ELMs.

关键词： Extreme learning machine minimum information divergence criterion kernel method gradient algorithm

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