搜索资源列表
非线性拟合算法
- 包含了各种给线性拟合算法
LS_SVM
- 最小二乘支持向量机,用于多元非线性回归分析,非线性拟合与预测-Least squares support vector machine for multi-linear regression analysis, nonlinear fitting and prediction
curvefit
- 用MATLAB函数进行非线性拟合，在VB中调用-MATLAB function with non-linear fitting, call in VB
fx_nihe
- 利用matlab对实验数据进行非线性拟合-Matlab on the experimental data using non-linear fitting
non-linear_fitting_algorithm
- 利用matlab对图像进行非线性拟合时的算法研究-Using matlab to the image when the non-linear fitting algorithm
lagrange
- 非线性拟合，可以根据已经数据，计算出对应的数据-Nonlinear fitting, can have data to calculate the corresponding data
FSQ
- 实现数据的非线性拟合,完成曲线的拟合，让用户不用操心-Nonlinear fitting data to complete the curve fitting, so that users do not have to worry about
nihe
- 详细介绍在matlab中如何实现非线性拟合，内附例子-Details of how to achieve the non-linear fitting matlab
BPNeuralforNonlinear
- 使用BP神经网络做非线性拟合，它有很强的拟合功能，应用面很广。-The BP neural network to do non-linear fitting, it has a strong fit function, the application was very broad.
遗传算法优化BP神经网络-非线性函数拟合
- 进行非线性函数拟合且用遗传算法对BP神经网络进行优化(The nonlinear function is fitted and the BP neural network is optimized by genetic algorithm)
MATLAB求解非线性最小二乘法拟合问题 源程序代码
- MATLAB求解非线性最小二乘法拟合问题 源程序代码(MATLAB solving nonlinear least squares method of fitting the source code)
非线性拟合
- 非线性拟合,stats第二个数为F分布值 finv(0.95,1,9) %F分布查表值(Nonlinear fitting, stats second number is F, distribution value finv (0.95,1,9)%F distribution look-up table value)
遗传算法优化BP神经网络-非线性函数拟合
- 遗传算法优化BP神经网络-非线性函数拟合(Genetic algorithm optimization BP neural network nonlinear function fitting)
NonlinearFittingLIVE
- 该算法实现了数据的非线性拟合，适合各种初值，(The algorithm implements nonlinear fitting of data)
BP神经网络的非线性系统建模-非线性函数拟合
- BP神经网络的非线性系统建模-非线性函数拟合(Nonlinear system modeling of BP neural network nonlinear function fitting)
BP神经网络用于非线性函数拟合
- BP神经网络用于非线性函数的拟合，效果不错，适合初学者。(BP neural network for nonlinear function fitting, the effect is good, suitable for beginners.)
第8章 数据拟合
- 数据拟合，回归算法，一次回归，多次回归，线性拟合，非线性拟合(Data fitting, regression algorithm, primary regression, multiple regression, linear fitting, nonlinear fitting)
xianxing
- 该代码主要用于非线性拟合，并举例指出如何运用。(Example of nonlinear fitting)
拟合
- 多个函数的曲线拟合，里面统计有最小二乘、非线性回归(Curve fitting for multiple functions)
第三题程序和结果
- 用rstool进行多变量非线性拟合 题目：问题3：在某地夏天室内环境下，使用可变环境因素（干球温度、相对湿度及风速）与体感温度（红字）对照表（见表3）中的数据作为数据源，请挖掘出可变环境因素与体感温度之间的关系，并进行误差分析。 表3可控环境因素对体感温度对照表 干球温度℃ 相对湿度% 风速FPM(1FPM=0.00508m/s) 0 100 200 300 400 500 35 30 35 31.6 26.1 23.8 22.7 22.2 40 35 31.9 26.4 24