搜索资源列表
leiling_v80
- 利用最小二乘法进行拟合多元非线性方程,借鉴了主成分分析算法(PCA),用MATLAB实现动态聚类或迭代自组织数据分析。- Multivariate least squares fitting method of nonlinear equations, It draws on principal component analysis algorithm (PCA), Using MATLAB dynamic clustering or iterative self-organizing data
fengjeng_v42
- 用MATLAB实现动态聚类或迭代自组织数据分析,利用最小二乘法进行拟合多元非线性方程,仿真效率很高的。- Using MATLAB dynamic clustering or iterative self-organizing data analysis, Multivariate least squares fitting method of nonlinear equations, High simulation efficiency.
paopui_v58
- 利用最小二乘法进行拟合多元非线性方程,用MATLAB实现动态聚类或迭代自组织数据分析,计算时间和二维直方图。- Multivariate least squares fitting method of nonlinear equations, Using MATLAB dynamic clustering or iterative self-organizing data analysis, Computing time and two-dimensional histogram.
manning_v18
- 插值与拟合,解方程,数据分析,利用最小二乘法进行拟合多元非线性方程,matlab编写的元胞自动机。- Interpolation and fitting, solution of equations, data analysis, Multivariate least squares fitting method of nonlinear equations, matlab prepared cellular automata.
bunfui
- 借鉴了主成分分析算法(PCA),利用最小二乘法进行拟合多元非线性方程,matlab程序运行时导入数据文件作为输入参数。- It draws on principal component analysis algorithm (PCA), Multivariate least squares fitting method of nonlinear equations, Import data files as input parameters matlab program is running.
mun_gc34
- 独立成分分析算法降低原始数据噪声,课程设计时编写的matlab程序代码,利用最小二乘法进行拟合多元非线性方程。- Independent component analysis algorithm reduces the raw data noise, Course designed to prepare the matlab program code, Multivariate least squares fitting method of nonlinear equations.
machine learning-matlab
- 机器学习是一门强大的语言,可以拟合、仿真、预测 各类数据之间的非线性映射,并揭示彼此间的联系(Machine learning is a powerful language that can fit, simulate, and predict the nonlinear mapping of various data and reveal the relationship between each other.)
RBF非线性拟合示例
- 利用matlab神经网络工具箱,实现对非线性数据的多输入多输出拟合
数学建模的29个通用模型及matlab解法
- 第一章 线性规划 第二章 整数规划 第三章 非线性规划 第四章 动态规划 第五章 图与网络 第六章 排队论 第七章 对策论 第八章 层次分析法 第九章 插值与拟合 第十章 数据的统计描述和分析 第十一章 方差分析 第十二章 回归分析(Chapter I linear programming Chapter II integer programming Chapter III nonlinear programming Chapter IV dynamic planning Chapt