搜索资源列表
trizj
- trizj.m为三转角法插值逼近三次样条函数-trizj.m corner of France for the three cubic spline interpolation function approximation
RBF_sin
- 自定义RBF网络，逼近y=sin(t)函数用例。-User defined RBF Neural network,take y=sin(t) as a test example
Fourier-series
- 周期函数傅里叶级数展开相关的函数M文件，Fouriers( )、Fouriers2( )分别为非分段和分段函数的部分和（n阶），Fouriersp( )Fouriersp2( )为相应的的3阶、5阶、10阶傅里叶逼近，piecewise( )为分段函数-Fourier series expansion of periodic functions related function M-files, Fouriers (), Fouriers2 () functions, respectively,
neural-network-example
- 用前向神经元网络逼近连续函数，f（x1，x2，x3，x4）=sinx1+sinx2+sinx3+sinx4 定义域为[0,2*pi].刘宝碇老师例子仅供参考-Let us design a feedforward NN to approximate the continuous function, f(x1, x2, x3, x4) = sin x1+ sin x2+ sin x3+ sin x4 defined on [0, 2*pi]4.
square_approximat
- 编写函数最佳平方逼近的程序square_approximat-Write a function square approximation procedure square_approximat
chap10
- 使用RBF网络逼近y(k)=u(k)^3+y(k-1)/1+y(k-1)^2,遗传算法优化程序chap10_3a.m,RBF网络逼近函数子程序chap10_3b.m和chap10_3c.m-Using RBF network approximation y (k) = u (k) ^ 3+y (k-1)/1+y (k-1) ^ 2, genetic algorithm optimization procedures chap10_3a.m, RBF network approximation f
ff
- BP算法例子：用一个五层的神经网络去逼近函数 ，有需要的程序员可以用到。-BP algorithm examples: using a neural network to approximate five functions, there is a need for programmers to use.
BPbijin
- 自己写的BP网络逼近非线性函数的matlab的m文件，没有调用matlab现成的函数-Write your own BP neural network nonlinear function approximation matlab m-file, there is no ready-made call matlab function
RBF
- rbf神经网络主要用于非线性函数的逼近，经过测试R2010能够使用-rbf neural network nonlinear function fitting
BP2
- 三层BP神经网络来完成非线性函数的逼近任务-BP neural network to complete the task of nonlinear function approximation
BPFuncApproximation
- BP神经网络训练程序，基于梯度学习算法，对非线性函数（hermitian）逼近。-The BP neural network training program，which is based on the steepest descent Method，，，backpropagation network (BP) approximation of the nonlinear function。
RBF
- 适用于径向基网络初学者,是一个关于逼近hermit函数的源程序-applied to the new learner of RBF
bp
- 利用BP神经网络来逼近hermit函数的源程序，适用于初学bp的研究者-applied to new learner of bp ,hermit
BP
- 使用C语言模拟实现bp神经网络逼近正弦函数-Using C language to achieve BP network approximation analog sine function
2
- 提升复杂系统的定量决策支持，将成本作为独立变量（CAIV）寻求“最佳”点设计，是一个约束的非线性优化问题，其目标函数是最优有效性度量（MOE）表示，由基于性能的成本模型、二阶约束MOEs、系统性能指标的界限（MOPs）构成。算法采用的是同时扰动随机逼近方法（SPSA）。附件中是二阶约束MOEs模型的仿真程序。附：仿真流程图-Ascend the quantitative decision support of complex systems, will cost as an independen
BP
- BP神经网络 搭建神经网络来逼近非线性函数-BP neural network to build a neural network to approximate nonlinear functions
bpNNbijinERYUANhanshuSANWEITU
- BP神经网络实现二元函数的逼近源程序代码-BP neural network source code binary function approximation
RBF_matlab
- 用MATLAB编写的RBF神经网络程序，能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性.-Using MATLAB RBF neural network program that can approximate any nonlinear function that can handle difficult analytic regularity within the system.
Neural-Network-Algorithm
- 神经网络学习对于逼近实数值、离散值或向量值的目标函数提供了一种健壮性很强的方法 -Neural network learning approach for real values, discrete values or provide a strong method to measure the robustness of the objective function
SmartYTBJ
- 使用matlab进行函数插值逼近的例程，效果很好，有注释，易读性好！-Using matlab function interpolation approximation routines, well, there are notes, legibility is good!