Description: 用最小二乘法来进行函数模拟。对输入的数据构造一个多项式。-using the method of least squares to function simulation. Of input data structure a polynomial. Platform: |
Size: 412672 |
Author:liuhua |
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Description: 最小二乘的C语言程序－最小二乘原理学习参考的好例子。-Least-squares of C language programming- the principle of least squares learning a good example of reference. Platform: |
Size: 3072 |
Author:纪晓岚 |
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Description: 建立了一种基于移动最小二乘(Moving Least-Squares MLS)法的曲线曲
面拟合方法这种方法对传统的最小二乘(LS)法的作了比较大的改进使生成的曲线曲面具
有精度高光滑性好等许多优点详细介绍了移动最小二乘法的原理应用和特点并且给
出了使用移动最小二乘法进行曲线曲面拟合的程序设计流程最后给出了曲线拟合和空间散
乱数据曲面拟合算例将拟合结果与最小二乘拟合结果作了比较分析了MLS 拟合曲线曲
面的光滑性和拟合质量表明了该方法的优越性和有效性-The establishment of a Mobile-based least squares (Moving Least-Squares MLS) method of curve and surface fitting method to the traditional method of least squares (LS) method were compared for improvement so that curves and surfaces generated with a precision high smoothness of the advantages of a good many details of the principle of moving least square method and given the characteristics of applications and the use of moving least square method of curve and surface fitting procedure is given the final design process and the space curve fitting scattered data surface to be Fitting the results of cases will be cost-effective and least square fitting results of a comparative analysis of the MLS fitting of smooth curves and surfaces and fitting quality demonstrates the superiority of the method and effectiveness of Platform: |
Size: 467968 |
Author:chenruibao |
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Description: 建立了一种基于移动最小二乘(Moving Least-Squares MLS)法的曲线曲
面拟合方法 这种方法对传统的最小二乘(LS)法的作了比较大的改进 使生成的曲线曲面具
有精度高 光滑性好等许多优点 详细介绍了移动最小二乘法的原理 应用和特点 并且给
出了使用移动最小二乘法进行曲线曲面拟合的程序设计流程 最后给出了曲线拟合和空间散
乱数据曲面拟合算例 将拟合结果与最小二乘拟合结果作了比较 分析了 MLS 拟合曲线曲
面的光滑性和拟合质量 表明了该方法的优越性和有效性-Was established based on moving least square (Moving Least-Squares MLS) method of this curve and surface fitting method to the traditional method of least squares (LS) method was relatively large improvements to make the generated curves and surfaces with a precision of High smoothness, good detail, and many other advantages of the principle of least-squares method for mobile applications and features and gives the least-squares method using the mobile curve and surface fitting procedure design process Finally, curve fitting and spatial scattered data surface to be cost-effective cases of the results of the fitting results are compared with the least-squares fitting analysis of MLS fitting curves and surfaces smooth and fitting quality demonstrates the superiority and effectiveness of the method Platform: |
Size: 467968 |
Author:李秀丽 |
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Description: * FILE: least-squares.c
* This program computes a linear model for a set of given data.
*
* PROBLEM DESCRIPTION:
* The method of least squares is a standard technique used to find
* the equation of a straight line from a set of data. Equation for a
* straight line is given by
* y = mx + b
* where m is the slope of the line and b is the y-intercept.
*
* Given a set of n points {(x1,y1), x2,y2),...,xn,yn)}, let
* SUMx = x1 + x2 + ... + xn
* SUMy = y1 + y2 + ... + yn
* SUMxy = x1*y1 + x2*y2 + ... + xn*yn
* SUMxx = x1*x1 + x2*x2 + ... + xn*xn
*
* The slope and y-intercept for the least-squares line can be
* calculated using the following equations:
* slope (m) = ( SUMx*SUMy - n*SUMxy ) / ( SUMx*SUMx - n*SUMxx )
* y-intercept (b) = ( SUMy - slope*SUMx ) / n
*
* AUTHOR: Dora Abdullah (Fortran version, 11/96)
* REVISED: RYL (converted to C, 12/11/96)- * FILE: least-squares.c
* This program computes a linear model for a set of given data.
*
* PROBLEM DESCRIPTION:
* The method of least squares is a standard technique used to find
* the equation of a straight line from a set of data. Equation for a
* straight line is given by
* y = mx + b
* where m is the slope of the line and b is the y-intercept.
*
* Given a set of n points {(x1,y1), x2,y2),...,xn,yn)}, let
* SUMx = x1 + x2 + ... + xn
* SUMy = y1 + y2 + ... + yn
* SUMxy = x1*y1 + x2*y2 + ... + xn*yn
* SUMxx = x1*x1 + x2*x2 + ... + xn*xn
*
* The slope and y-intercept for the least-squares line can be
* calculated using the following equations:
* slope (m) = ( SUMx*SUMy - n*SUMxy ) / ( SUMx*SUMx - n*SUMxx )
* y-intercept (b) = ( SUMy - slope*SUMx ) / n
*
* AUTHOR: Dora Abdullah (Fortran version, 11/96)
* REVISED: RYL (converted to C, 12/11/96) Platform: |
Size: 1024 |
Author:xuwenhao2005 |
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Description: 加权最小二乘法的原理 应用及其运算方式方法-Applying the principle of weighted least squares method and the ways and means of operation Platform: |
Size: 25600 |
Author:zhang |
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Description: 在多核处理器计算机上实现的多线程INSAR相位解缠，具体解缠方法为最小二乘法。-Multi-core processors to achieve multi-threaded computer INSAR phase unwrapping, unwrapping method for the specific method of least squares. Platform: |
Size: 4474880 |
Author:dawd |
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Description: A hybrid least squares support vector
machines and GMDH approach for river
fl ow forecasting-This paper proposes a novel hybrid forecasting model, which combines the group
method of data handling (GMDH) and the least squares support vector machine
(LSSVM), known as GLSSVM. The GMDH is used to determine the useful input vari-
ables for LSSVM model and the LSSVM model which works as time series forecasting. 5
In this study the application of GLSSVM for monthly river fl ow forecasting of Selangor
and Bernam River are investigated. The results of the proposed GLSSVM approach
are compared with the conventional artifi cial neural network (ANN) models, Autoregres-
sive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the
long term observations of monthly river fl ow discharge. The standard statistical, the 10
root mean square error (RMSE) and coe ffi cient of correlation (R) are employed to eval-
uate the performance of various models developed. Experiment result indicates that
the hybrid model was powerful tools to mo Platform: |
Size: 1467392 |
Author: |
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Description: 最小二乘法，递推最小二乘法，基本最小二乘法，帮助同学学习最小二乘法。-The method of least squares, recursive least squares method, the basic method of least squares, to help students learn the method of least squares. Platform: |
Size: 692224 |
Author:rose |
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Description: 用m语言写的最小二乘法的算法，可以直接嵌入系统中计算，简单方便-use m language to write the method of least squares algorithm, can be directly embedded systems calculation is simple and convenient Platform: |
Size: 1024 |
Author:王静雯 |
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Description: 最小二乘法辨识原理 是个ppt 讲的不错！！看看吧-The principle of the method of least squares identification is good! ! Look at it Platform: |
Size: 5980160 |
Author:王某 |
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Description: 利用最小二乘法的原理高精度估计正弦波信号的幅值，频率和初相-The principle of using the least squares method estimated sine wave signal amplitude, frequency and initial phase of high-precision Platform: |
Size: 2727936 |
Author:罗知亮 |
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Description: 用matlab所学的知识，编写最小二乘法拟合程序，以解决物理实验中的最小二乘法拟合曲线以及相关系数等的问题。-With matlab learned, the preparation method of least squares fitting procedure to solve the problems of the least-squares fitting curve and correlation coefficient physics experiments. Platform: |
Size: 72704 |
Author:邓棋文 |
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Description: 辨识算法分别用一次最小二乘算法和递推最小二乘算法对被控对象进行辨识。最小二乘法是一种数学优化技术。-Identification algorithm using a least squares algorithm, respectively, and the recursive least squares algorithm to identify the controlled object. Method of least squares is a mathematical optimization techniques. Platform: |
Size: 6144 |
Author:gjf |
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Description: 函数逼近与曲线拟合，用最小二乘法进行曲线拟合的C或C++编写的完整程序！-C language prepared by the method of least squares curve fitting Platform: |
Size: 5120 |
Author:刘长青 |
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Description: matlab最小二乘法代码。1~4分别是一次算法、地推算法、增广最小二乘和辅助变量。-east squares method matlab code. 1 to 4 are the first algorithm to calculate method of least squares and augmented auxiliary variables. Platform: |
Size: 7168 |
Author:夏承成 |
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Description: 最小二乘法是系统辨识中最经典的方法，它通过最小化误差的平方和寻找数据的最佳函数匹配。利用最小二乘法可以简便地求得未知的数据，并使得这些求得的数据与实际数据之间误差的平方和为最小。最小二乘法还可用于曲线拟合。其他一些优化问题也可通过最小化能量或最大化熵用最小二乘法来表达。其中，RLS是递推最小二乘法程序，ELS是增广递推最小二乘法的程序。-
System identification least squares method is the most classic method, which matches the data by squaring and finding the best to minimize the error function. Least squares method can be easily calculated unknown data, and make the square error between the actual data and the data obtained and the minimum. Least squares method can be used for curve fitting. Some other optimization problems can be expressed using the method of least squares by minimizing energy or maximizing entropy. Wherein, RLS is a recursive least squares program, ELS is augmented recursive least squares method procedures. Platform: |
Size: 2048 |
Author:原文宾 |
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Search - method of least squares