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cmac_xz
- 二维CMAC神经网络逼近函数源代码，算法清晰，注释很全，是学习CMAC神经网络的不二之选-CMAC neural network learning choice for the two-dimensional approximation of the function CMAC neural network source code, algorithms clear, very full notes, is
NNH
- 神经网络作业，使用神经网络对函数进行逼近,函数是由随机序列产生-Neural network operations, the use of neural network function approximation, the function is generated by the random sequence
program
- 模型逼近的机械手网络的自适应滑模控制器程序控制器函数子程序-Adaptive sliding mode controller program controller function subprogram model approximation robot networks
lagrange-interpolation
- lagrange多项式插值，满足插值条件的函数去逼近原函数-lagrange polynomial interpolation
123
- 利用三层BP神经网络来完成非线性函数的逼近任务，其中隐层神经元个数为五个。-To complete the task of nonlinear function approximation by three layers of BP neural network, in which the number of hidden layer neurons into five.
chazhi
- 对函数进行插值计算，与逼近的算法及其类似，可以与之前上传的程序进行对比分析。-Interpolation of functions, and approximation algorithms and the like, can be used with the program before uploading comparative analysis.
rbf
- 建立一个径向基神经网络，对非线性函数y=sqrt(x)进行逼近，并作出网络的逼近误差-The establishment of a radial basis function neural network, the nonlinear function y = sqrt (x) to approximate, and make the network approximation error
Coordination-and-Optimization
- 将网损价格因子和网损协调系数引入目标函数,建立了改进直流潮流模型,实现了负荷在机组间的最优分配 利用交流潮流方法计算系统实际网损,并利用增量直流潮流模型将网损在机组间进行合理分摊 最后利用交直流迭代思想修正网损价格因子和网损协调系数以优化网损分配方案。IEEE14节点和IEEE118节点算例验证了该方法的可行性,算例结果充分逼近了交流最优潮流的计算结果,符合实际系统运行状况。-The net loss and net loss of coordination price factor intro
sample2
- 非线性映射能力：BP神经网络实质上实现了一个从输入到输出的映射功能，数学理论证明三层的神经网络就能够以任意精度逼近任何非线性连续函数。这使得其特别适合于求解内部机制复杂的问题，即BP神经网络具有较强的非线性映射能力-Nonlinear mapping ability: BP neural network essentially implements a mapping from input to output function, the mathematical proof of the thr
sample6
- 非线性映射能力：BP神经网络实质上实现了一个从输入到输出的映射功能，数学理论证明三层的神经网络就能够以任意精度逼近任何非线性连续函数。这使得其特别适合于求解内部机制复杂的问题，即BP神经网络具有较强的非线性映射能力-Nonlinear mapping ability: BP neural network essentially implements a mapping from input to output function, the mathematical proof of the thr
filter1
- 通过FIR滤波器的自适应调整，不断修正其系统函数，使其与未知系统的参数充分逼近，从而使误差最小，达到系统辨识的目的。-Through adaptive FIR filter, constantly revised its system functions to an unknown system parameters and adequate approximation, so that the error is minimized to achieve system identificatio
Newton-iterative-method
- 牛顿迭代法解非线性函数的基本思路是通过曲线上任意点的切线来逼近函数的根-The basic ideas of Newton iterative method for solving nonlinear function is through the tangent at any point on the curve to approximate the function of root
newrb
- 演示如何应用newrb函数构建一个径向网络，并对一系列数据进行逼近- Demonstrates how to apply newrb build a radial network function, and approximate number of data
Equation-Root-dichotomy
- 二分法，又称分半法，是一种方程式根的近似值求法。对于区间[a,b]上连续不断且f(a) ·f(b)<0的函数y=f(x)，通过不断地把函数f(x)的零点所在的区间一分为二，使区间的两个端点逐步逼近零点，进而得到零点近似值的方法叫做二分法(bisection)。-Equation Root dichotomy
approxfcn
- 逼近函数 使用查找表的方式来进行函数处理，使得函数G逼近函数F-a function handle, G, that approximates the function handle F by using a lookup table.
BPNN
- bp神经网络逼近测试函数d=sin(2πx)sin(2πy)-The bp neural network approximation test function d = sin (2 PI x) sin (2 PI y)
LVBO
- 分别使用矩形窗和汉明窗函数设计一个线性相位FIR低通滤波器，使其逼近理想低通滤波器的频率特性。采用频率抽样法设计FIR数字低通滤波器滤波器。-Using rectangular window and hamming window function to design a linear phase FIR low-pass filter, the frequency characteristics of the ideal low-pass filter. Frequency sampling m
matlab-function
- 数值分析中各种代码几何，包括差值函数，牛顿逼近，以及微分方程的解。所以优化参考。-Numerical analysis of various geometric code, including the difference between the functions, Newton approximation, as well as solving differential equations. So Optimization Reference.
cmac
- camac神经网络逼近函数,函数主要为z=(X^2+Y^2)*SIN(2*PI*X)-camac neural network approach, function primarily as z = (X ^ 2+Y ^ 2)* SIN (2* PI* X)
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- 单隐层神经网络学习实现给定函数的逼近 并选取测试点测试逼近效果-Single hidden layer neural network learning approach to achieve a given function and the Test Point Test approximation results