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New least-squares algorithm for model parameters estimation using self-potential anomalies

COMPUTERS & GEOSCIENCES 2008年第11期34卷 1569-1576页

作者： Abdelrahman, El-Sayed M. Essa, Khalid S. Abo-Ezz, Eid R. Sultan, Mohamed Sauck, William A. Gharieb, Abdelmohsen G. Cairo Univ Fac Sci Dept Geophys Giza Egypt Western Michigan Univ Coll Arts & Sci Dept Geosci Kalamazoo MI 49008 USA Nucl Mat Author Cairo Egypt

We have developed a new least-squares minimization approach to depth determination from self-potential (SP) data. By defining the anomaly value at the origin and at any two symmetrical points around the origin on the profile, the problem of depth determination from the residual SP anomaly has been transformed into finding a solution to a nonlinear equation of the form f(z) = 0. Procedures are also formulated to estimate the polarization angle, amplitude coefficient and the shape of the buried structure (shape factor). The method is simple and can,be used as a rapid method to estimate parameters that produced SP anomalies. The method is tested on synthetic data with and without random errors. It is also applied to a field example from Turkey. In all cases, the model parameters obtained are in good agreement with actual ones. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Self-potential anomaly Model parameters determination least-squares algorithm

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Adaptive line enhancers on the basis of least-squares algorithm for a single sinusoid detection

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1999年第8期E82A卷 1536-1543页

作者： Matsuura, K Watanabe, E Nishihara, A Tokyo Inst Technol Fac Engn Tokyo 1528552 Japan Shibaura Inst Technol Fac Syst Engn Ohmiya 3308570 Japan

This paper proposes adaptive line enhancers with new coefficient update algorithms on the basis of least-square-error criteria. Adaptive algorithms by least-squares are known to converge faster than stochastic-gradient ones. However they have high computational complexity due to matrix inversion. To avoid matrix inversion the proposed algorithms adapt only one coefficient to detect one sinusoid. Both FIR and IIR types of adaptive algorithm are presented, and the techniques to reduce the influence of additive noise is described in this paper. The proposed adaptive line enhancers have simple structures and show excellent convergence characteristics. While the convergence of gradient-based algorithms largely depend on their stepsize parameters, the proposed ones are free from them.

关键词： adaptive line enhancer least-squares algorithm frequency estimation

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k-space weighted least-squares algorithm for accurate and fast motion extraction from magnetic resonance navigator echoes

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MAGNETIC RESONANCE IN MEDICINE 2001年第5期46卷 1037-1040页

作者： Nguyen, TD Wang, Y Watts, R Mitchell, I Cornell Univ Weill Med Coll Dept Radiol New York NY 10021 USA

Navigator echoes provide an effective method to monitor physiological motion, allowing motion artifacts to be suppressed by modifying the data acquisition accordingly. The displacement can be measured directly from the navigator phase using an algorithm suggested by Ahn and Cho. Although computationally efficient, it is susceptible to noise, particularly contributions from points at the edges of k-space. A k-space weighted least-squares (kLS) algorithm is proposed which fits a straight line to the motion-induced phase shift. The linear fit is weighted strongly to high SNR points near the k-space center and only weakly to the poor SNR points at the edges of k-space. This algorithm was found to be as efficient as Ahn's algorithm but more robust against noise. (C) 2001 Wiley-Liss, Inc.

关键词： navigator motion detection least-squares algorithm motion artifacts k-space

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Identification of Structural Dynamic Parameters Using Block Pulse Functions and Recursive least-squares algorithm

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING 2017年第2期41卷 149-158页

作者： Ajorloo, Yaser Hosseini Ghaffarzadeh, Hosein Univ Tabriz Fac Civil Engn Tabriz Iran

System identification in recent years with the development of dynamic testing of structures has become one of the useful methods for structural health monitoring and damage detection and also finite element model updating. Identification of structural dynamic parameters is performed by using excitation-response data and includes physical parameters such as mass, stiffness and damping matrices and/or modal parameters such as natural frequencies, damping ratios and modal shapes. This paper presents a new method to identify the dynamical parameters of shear building based on continuous-time state-space estimation using block pulse functions and least-squares technique. Block pulse functions are a set of orthogonal functions with piecewise constant values and useful tools in analysis, identification and system science. Assuming that the input-outputs data of the original system are known, their block pulse coefficients can be calculated by numerical methods, and using block pulse operational matrix, state-space equations of dynamical system are transformed into block pulse regression equations. Based on these equations, the plant matrix is estimated using least-squares algorithm. Then, the physical and modal parameters of structure are identified based on eigenmode data of the estimated plant matrix. To prove the validity and feasibility of the proposed method, numerical simulation of a shear building which is equipped with sensors on all floors and excited by four different normally distributed random signals and an earthquake is presented. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.

关键词： System identification Block pulse functions Continuous-time state space least-squares algorithm Eigenmode data

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Accuracy of Synchrophasor Estimation Returned by a Frequency-Domain Linear least-squares algorithm 13

Accuracy of Synchrophasor Estimation Returned by a Frequency...

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13th International Symposium on Electronics and Telecommunications (ISETC)

作者： Belega, Daniel Petri, Dario Dallet, Dominique Univ Politehn Timisoara Dept Measurements & Opt Elect Timisoara Romania Univ Trento Dept Ind Engn Trento Italy Univ Bordeaux Bordeaux IPB IMS Lab Talence France

ISBN: (纸本)9781538659250

In this paper the accuracy of the synchrophasor estimator returned by the enhanced frequency-domain linear least-squares (e-FLLS) algorithm recently proposed in the scientific literature is investigated. Harmonically distorted or modulated electrical signals at off-nominal frequency are considered either in the presence or absence of additive wide-band noise. The e-FLLS algorithm is based on the rectangular window and it estimates the phasor amplitude and phase using three Discrete Fourier Transform (DFT) samples. It effectively reduces the detrimental contributions of both the fundamental image component and wide-band noise on the estimated parameters. The accuracies of the e-FLLS algorithm and the corrected Interpolated DFT (IpDFTc) algorithm are then compared to each other through computer simulations in different operating conditions. As accuracy parameter the Total Vector Error (TVE) is used.

关键词： error analysis interpolated DFT algorithm least-squares algorithm parameter estimation synchrophasor

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Modified Recursive least squares algorithm with Variable Parameters and Resetting for Time-Varying System

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Chinese Journal of Chemical Engineering 2002年第3期10卷 298-303页

作者：薛云灿钱积新 InstituteofSystemsEngineering DepartemtnofControlScienceandEngineeringZhejiangUniversityHangzhou310027China

Based on the idea of the set-membership identification, a modified recursive least squares algorithm with variable gain, variable forgetting factor and resetting is presented. The concept of the error tolerance level is proposed. The selection criteria of the error tolerance level are also given according to the min-max principle. The algorithm is particularly suitable for tracing time-varying systems and is similar in computational complexity to the standard recursive least squares algorithm. The superior performance of the algorithm is verified ma simulation studies on a dynamic fermentation process.

关键词： least-squares algorithm dynamic fermentation process parameter estimation identification

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Identification of Linear Time-Varying Systems Using a Modified least squares algorithm

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IFAC Proceedings Volumes 1998年第22期31卷 433-438页

作者： Rogelio Lozano Dimitrios Dimogianopoulos Robert Mahony Université de Technologie de Compiègne UMR - CNRS 6599 Heudiasyc Centre de Recherches de Royallieu BP 20529 60205 Compiegne Cedex

In the present paper a modified version of the standard LS algorithm is proposed. The aim is to establish a series of convergence properties on the identification error, the parameter estimates and the covariance matrix. Thus the proposed modification renders the LS algorithm suitable for use in LTV *** is important in an adaptive control context as LS algorithms provide an easy way of modifying the parameter estimates in order to avoid singular points in the control law (namely by using the “covariance᾿ matrix).

关键词： Time-varying systems least-squares algorithm Covariance matrix Identification

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Adaptive Identification Via A Modified least–squares algorithm

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International Journal of Modelling and Simulation 1992年第1期12卷 8-13页

abstractabstractThe authors present an adaptive identification method (AIM) primarily for adaptive control systems with insufficient persistent excitation. In this paper, the matrix P(t-l) resetting, a new forgelling factor λ(1), remembering units, and a weighted filtering algorithm are proposed. The AIM technique, using a modified least squares algorithm, is presented in terms of the previously mentioned procedures. Theoretical analyses and simulation results demonstrate that the proposed methodology can overcome the bursting problems thaI sometimes exisl in adaptive control systems.

关键词： Identification least-squares algorithm adaptive control systems bursting excitation simulation

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Process Flow Identification Method using a Self Tuning least squares algorithm

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IFAC Proceedings Volumes 1995年第24期28卷 353-355页

作者： Florin Ionescu Florin Hasler Department of Mechanical Engineering Fachhochschule Konstanz Germany

The plane least squares algorithm has a relative good convergence to the stationary value of a process. Not the same about those which detains random flow mode changes or parameter slithering with comparable orders with the process noises. The method has appeared as solution of a practical on-line identification problem of a technological flow for an accurate row materials dosage. The usage of the low performances existing computing resources is a sine-qua-non condition.

关键词： Process identification least-squares algorithm Dynamic behaviour Insensitivity Switching algorithms

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Use of two-stage least-squares algorithms for identification of continuous systems with time delay based on pulse responses

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AUTOMATICA 2004年第9期40卷 1561-1568页

作者： Hwang, SH Lai, ST Natl Cheng Kung Univ Dept Chem Engn Tainan 70101 Taiwan

This paper presents the so-called two-stage least-squares algorithms to deal with practical identification difficulties often encountered in field testing, such as unsteady initial states, unknown load disturbances, and noise-corrupted measurement. For step and ramp responses, a general linear regression equation is derived from multiple integration of the differential system equation. Four types of pulse inputs are then considered, each of which has its specific advantage in applications and can be represented as a combination of step or ramp inputs. Based on any of these pulse responses, the algorithms are able to overcome those difficulties and yield accurate parameter estimates in a sequential manner. The resulting identification scheme provides a convenient way to give the delay estimate along with system parameters and is robust with respect to noise and model structure mismatch. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： pulse response least-squares algorithm delayed system integral transform unknown disturbance

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