scholarly journals The Parameter Estimation of Double Exponential Pulse Based on a Least Infinity Norm Fitting Method

2021 ◽  
Vol 2083 (4) ◽  
pp. 042002
Author(s):  
Yuewu Shi ◽  
Wei Wang ◽  
Zhizhen Zhu ◽  
Xin Nie
Keyword(s):  
Estimation Error ◽  
Estimation Method ◽  
Maximum Amplitude ◽  
Least Square Method ◽  
Least Square ◽  
Physical Parameters ◽  
Infinity Norm ◽  
Fitting Method ◽  
Double Exponential ◽  
Exponential Pulse

Abstract This paper presents an estimation method of double exponential pulse (DEP) between the physical parameters rise time (t r), full width at half maximum amplitude (t FWHM) and the mathematical parameters α, β. A newly fitting method based on the least infinity norm criterion is proposed to deal with the estimation problem of DEP. The calculation process and equation of parameters of this method is proposed based on an m-th-order polynomial fitting model. This estimation method is compared with the least square method by the same data and fitting function. The results show that the maximum estimation error of parameters of double exponential pulse obtained by the least infinity norm method is 1.5 %.

scholarly journals A New Physical Parameter Identification Method for Two-Axis On-Road Vehicles: Simulation and Experiment

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Minyi Zheng ◽  
Peng Peng ◽  
Bangji Zhang ◽  
Nong Zhang ◽  
Lifu Wang ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Parameter Identification ◽  
Physical Parameter ◽  
Mass Matrix ◽  
Estimation Method ◽  
Least Square Method ◽  
Least Square ◽  
Percentage Error ◽  
Physical Parameters ◽  
Identification Method

A new physical parameter identification method for two-axis on-road vehicle is presented. The modal parameters of vehicle are identified by using the State Variable Method. To make it possible to determine the matricesM,C, andKof the vehicle, a known mass matrixΔMis designed to add into the vehicle in order to increase the number of equations ensuring that the number of equations is more than the one of unknowns. Therefore, the physical parameters of vehicle can be estimated by using the least square method. To validate the presented method, a numerical simulation example and an experiment example are given in this paper. The numerical simulation example shows that the largest of absolute value of percentage error is 1.493%. In the experiment example, a school bus is employed in study for the parameter identification. The simulation result from full-car model with the estimated physical parameters is compared with the test result. The agreement between the simulation and the test proves the effectiveness of the proposed estimation method.

Cutting Force Empirical Model of High-Speed Precision Hard Cutting GCr15

2009 ◽  
Vol 69-70 ◽  
pp. 301-305
Author(s):  
Jing Shu Hu ◽  
Yuan Sheng Zhai ◽  
Fu Gang Yan ◽  
Yu Fu Li ◽  
Xian Li Liu
Keyword(s):  
Cutting Force ◽  
Empirical Model ◽  
High Speed ◽  
Orthogonal Design ◽  
Cutting Speed ◽  
Least Square Method ◽  
Cutting Parameters ◽  
Least Square ◽  
Physical Parameters ◽  
Hard Cutting

In the cutting process, cutting force is one of the important physical parameters, which affects the generation of cutting heat, tool life and surface precision of workpiece directly. In this paper an orthogonal design of experiment and subsequent data is analyzed using high speed finish hard cutting GCr15 whose hardness is 65HRC. Cutting speed is 200-400m/min, to study the influence of cutting parameters on cutting force, cutting force empirical model has obtained from least square method.

scholarly journals Calculation and realization of new method grey residual error correction model

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254154
Author(s):  
Lifang Xiao ◽  
Xiangyang Chen ◽  
Hao Wang
Keyword(s):  
Prediction Model ◽  
Least Square Method ◽  
Residual Error ◽  
Least Square ◽  
Grey Model ◽  
Grey Prediction ◽  
Grey Prediction Model ◽  
True Value ◽  
Prediction Function ◽  
Fitting Method

Aiming at the problem of prediction accuracy of stochastic volatility series, this paper proposes a method to optimize the grey model(GM(1,1)) from the perspective of residual error. In this study, a new fitting method is firstly used, which combines the wavelet function basis and the least square method to fit the residual data of the true value and the predicted value of the grey model(GM(1,1)). The residual prediction function is constructed by using the fitting method. Then, the prediction function of the grey model(GM(1,1)) is modified by the residual prediction function. Finally, an example of the wavelet residual-corrected grey prediction model (WGM) is obtained. The test results show that the fitting accuracy of the wavelet residual-corrected grey prediction model has irreplaceable advantages.

scholarly journals A New Distribution for Modeling Lifetime Data with Different Methods of Estimation and Censored Regression Modeling

2020 ◽  
Vol 8 (2) ◽  
pp. 610-630 ◽  
Author(s):  
Mohamed Ibrahim ◽  
Emrah Altun EA ◽  
Haitham M. Yousof
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Estimation Method ◽  
Least Square Method ◽  
Least Square ◽  
Likelihood Method ◽  
Survival Times ◽  
New Model ◽  
Von Mises ◽  
Bootstrapping Method

In this paper and after introducing a new model along with its properties, we estimate the unknown parameter of the new model using the Maximum likelihood method, Cram er-Von-Mises method, bootstrapping method, least square method and weighted least square method. We assess the performance of all estimation method employing simulations. All methods perform well but bootstrapping method is the best in modeling relief times whereas the maximum likelihood method is the best in modeling survival times. Censored data modeling with covariates is addressed along with the index plot of the modified deviance residuals and its Q-Q plot.

Reliability and Usefulness of the Fitting of a Modified Gamma Function to Time-Activity Curves by Means of a Non-Linear Iterative Least-Square Method

1981 ◽  
Vol 20 (04) ◽  
pp. 195-197
Author(s):  
J. M. Fránquiz
Keyword(s):  
Gamma Function ◽  
Least Square Method ◽  
Least Square ◽  
Base Line ◽  
Time Activity ◽  
Appearance Time ◽  
Least Square Fitting ◽  
Fitting Method ◽  
Non Linear ◽  
Least Square Fitting Method

A non-linear iterative least-square fitting method is presented for calculating the parameters of a modified gamma function. The method permits the correction of the appearance time (AT) and the curve parameters in those situations in which AT cannot be estimated with accuracy. The reliability and accuracy of the method is studied in experimental and simulated curves by means of a computer, comparing the results with those obtained by the method of Starmer and Clark for different initial selections of AT and noise at the base line. The usefulness of the method is shown in situations where the curves are distorted in their initial part.

scholarly journals Numerical approach for extraction of photovoltaic generator single-diode model parameters

2021 ◽  
Vol 2 (2) ◽  
pp. 58-66
Author(s):  
Abdelaaziz Benahmida ◽  
Noureddine Maouhoub ◽  
Hassan Sahsah
Keyword(s):  
Ideality Factor ◽  
Series Resistance ◽  
Least Square Method ◽  
Numerical Approach ◽  
Least Square ◽  
Physical Parameters ◽  
Model Parameters ◽  
Shunt Resistance ◽  
Key Points ◽  
Photovoltaic Generators

In this work, a numerical approach has been proposed to estimate the five single-diode circuit model physical parameters of photovoltaic generators from their experimental current-voltage characteristics. Linear least square method has been used to solve the system of three linear equations to express the shunt resistance, the saturation current and the photocurrent as a function of the series resistance and the ideality factor. Two key points have been used to solve the system of two nonlinear equations to extract values of series resistance and ideality factor. The advantage of the proposed method with respect of existing numerical techniques is that use only two key points of the experimental characteristic and need only two initial guesses and does not use any approximation. To evaluate the proposed method, three PV generators data have been used to compare the experimental and the theoretical curves. The application of the proposed method provides a good agreement with the experimental.

scholarly journals Comparison of M Estimation, S Estimation, with MM Estimation to Get the Best Estimation of Robust Regression in Criminal Cases in Indonesia

2022 ◽  
Vol 18 (2) ◽  
pp. 251-260
Author(s):  
Malecita Nur Atala Singgih ◽  
Achmad Fauzan
Keyword(s):  
Regression Analysis ◽  
Robust Regression ◽  
Estimation Method ◽  
Least Square Method ◽  
Influential Factors ◽  
Least Square ◽  
Method Of Moment ◽  
Best Estimate ◽  
M Estimation ◽  
Mm Estimation

Crime incidents that occurred in Indonesia in 2019 based on Survey Based Data on criminal data sourced from the National Socio-Economic Survey and Village Potential Data Collection produced by the Central Statistics Agency recorded 269,324 cases. The high crime rate is caused by several factors, including poverty and population density. Determination of the most influential factors in criminal acts in Indonesia can be done with Regression Analysis. One method of Regression Analysis that is very commonly used is the Least Square Method. However, Regression Analysis can be used if the assumption test is met. If outliers are found, then the assumption test is not completed. The outlier problem can be overcome by using a robust estimation method. This study aims to determine the best estimation method between Maximum Likelihood Type (M) estimation, Scale (S) estimation, and Method of Moment (MM) estimation on Robust Regression. The best estimate of Robust Regression is the smallest Residual Standard Error (RSE) value and the largest Adjusted R-square. The analysis of case studies of criminal acts in Indonesia in 2019 showed that the best estimate was the S estimate with an RSE value of 4226 and an Adjusted R-square of 0.98  

scholarly journals Path generation for flying robots in mountainous regions

2016 ◽  
Vol 9 (1) ◽  
pp. 44-60 ◽  
Author(s):  
Amirreza Kosari ◽  
Hossein Maghsoudi ◽  
Abolfazl Lavaei
Keyword(s):  
Numerical Technique ◽  
Estimation Method ◽  
Least Square Method ◽  
Least Square ◽  
Performance Criteria ◽  
Mission Design ◽  
Vertical Acceleration ◽  
Mountainous Regions ◽  
Terrain Following ◽  
Flying Robots

In this paper, a new path planning method is proposed to resolve the problem of two-dimensional terrain following flight of flying robots in mountainous regions. The performance criteria considered for this mission design could include either the minimum vertical acceleration or the minimum flying time. To impose the terrain following/terrain avoidance constraints, various approaches such as least square method, Fourier series method, Gaussian estimation method, and Chebyshev orthogonal polynomial are explored. The resulting optimal control problem is discretized by employing a numerical technique namely direct collocation and then transformed into a nonlinear programming problem. The efficacy of the proposed method is demonstrated by extensive simulations, and particularly, it has been verified that this method is able to produce a solution that satisfies all hard constraints of the underlying problem.

A New Method for the Identification of Coulomb and Viscous Friction

Tribology ◽  
2005 ◽  
Author(s):  
Lilan Liu ◽  
Hongzhao Liu ◽  
Ziying Wu ◽  
Daning Yuan
Keyword(s):  
Damping Ratio ◽  
Viscous Friction ◽  
Least Square Method ◽  
Least Square ◽  
New Method ◽  
Exponential Fitting ◽  
Viscous Damping ◽  
Equivalent Viscous Damping ◽  
Fitting Method ◽  
Friction Parameters

In this paper, a new method for simultaneously estimating Coulomb and viscous friction parameters from the free vibration of a damped oscillator is put forward. In the method, the nonlinear vibration equation with Coulomb and viscous friction is transformed into a linear procedure with equivalent viscous damping which is a function of velocity. The proposed method works well with both the displacement and velocity response data, while the case of zero velocity is not considered. From the displacement decaying curve, the equivalent viscous damping ratios are obtained by means of the local exponential fitting method, and different velocities corresponding to the equivalent viscous damping ratios are also obtained from the velocity decaying curve. Then, according to the relationship between the equivalent viscous damping ratio and the velocity, the Coulomb friction and the viscous damping are achieved using the least square method. The validity and accuracy of the proposed method are demonstrated through good simulation results.

Improved modified moving average analysis of T-wave alternans using least squares-based curve fitting method

2014 ◽  
Vol 07 (04) ◽  
pp. 1450044 ◽  
Author(s):  
Xiang-Kui Wan ◽  
Kang-Hui Yan ◽  
Ang Li ◽  
Ming-Hu Wu
Keyword(s):  
Curve Fitting ◽  
Moving Average ◽  
Least Square Method ◽  
Least Square ◽  
T Wave ◽  
Fitting Method ◽  
Average Analysis ◽  
T Wave Alternans ◽  
Improved Performance ◽  
Curve Fitting Method

T-wave alternans (TWA) in surface electrocardiograph (ECG) signal is considered a marker of abnormal ventricular function which may be associated with ventricular tachycardia. Several methods have been developed in recent years to evaluate the important feature. One such method is known as modified moving average (MMA) analysis, which performs well for different levels of TWA, but it is sensitive to the noise in T-waves. In this paper we propose an improved MMA algorithm, which adds a stage of T-wave curve fitting for the MMA method before intermediate averaging. The curve fitting is performed by means of least square method technique. Our assessment study demonstrates the improved performance.

Sign in / Sign up

Export Citation Format

Share Document