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shenjingwangluoxuexi
- 基于径向基RBF网络的函数逼近，通过在MATLAB环境下的编程、仿真，实现了对周期性函数的逼近-RBF network based on radial basis function approximation, by the MATLAB environment, programming, simulation, realization of the approximation of periodic functions
rbfSVM
- 基于RBF径向基核函数实现SVM支撑矢量机算法，-SVM algorithm based on RBF kernel
7
- 本文提出一种基于核方法的下视等分辨率景象匹配算法. 通过模拟电荷吸引模型, 提出了计算不等维高维数据相似度的SNN 核函数. 将图像中的特征点映射到径向基向量(Radial basis vector, RBV) 空间, 利用SNN 核函数计算两个特征点集的相似度及过渡矩阵. 利用置换测试模块来增强SNN 核的稳定性, 以确保输出解的可靠性. 实验证明, 基于SNN 核的景象匹配算法对图象畸变、噪声干扰与信号缺失具有很强的鲁棒性, 并可保证高精度与高实时性. -This paper prese
radial-basis-function-network
- 用于函数逼近的径向基逼近和差值，是一个基础函数，包括高斯及二项式两种，可拓展到多个应用领域-Radial basis functions are use for function approximation and interpolation. This package supports two popular classes of rbf: Gaussian and Polyharmonic Splines (of which the Thin Plate Spline is a subcla
score
- 对获得的512维小波特征进行了PCA降维处理，将特征空间降至100维，并采用前面得出的最佳系数针对多项式核函数和高斯径向基核函数-On access to the 512-dimensional wavelet features to reduce the dimension of the PCA, will feature space to 100 dimensions, and using the best coefficients obtained for the previous pol
NeuralNetwork_RBF
- RBF神经网络拟合 模式识别（径向基神经网络用于模式识别和函数拟合，陆振波）-RBF neural network pattern recognition fit (radial basis function neural networks for pattern recognition and function fitting, Lu Zhenbo)
impulse_rbe_test3
- 径向基网络法求解系统的脉冲响应函数，采用matlab编程实现，收敛速度快。-rbe net
2-2-2-4
- 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曲线-The establishment of a radial basis function neural network to approximate the nonlinear function y = sqrt (x), and make the network approximation error curve
1
- 使用newrb函数创建一个径向基网络实现函数拟合-To use newrb function to create a radial basis function network function fitting
twannnnpid533o
- 完善网络结构将RBF网络的径向基换成小波函数，调整权值和公式的变更，可望在仿真真结构中添加非奇异项以验证小波网络的辨识精度与能力，输入层加权值进行调整~..~ -Improve the network structure of RBF network of radial basis replaced by a wavelet function, adjust the weights and the formula change is expected to add a non-singula
svm(matlab)
- 一种新的函数拟合方法，在某些问题的近似程度上甚至优于径向基插值和Kriging插值方法-A new function fitting method, even better than the approximate extent of some of the issues radial basis interpolation and Kriging interpolation method
RBFNN-1
- 使用RBF神经网络实现函数逼近，逼近的函数为y(k)=u(k)^3+y(k-1)/(1+y(k-1)^2).通过对该程序的学习及实现可以更好的了解径向基神经网络的结构及算法-RBF neural network function approximation, the approximation of the function y (k) = u (k) ^ 3+y (k-1)/(1+y (k-1) ^ 2) through the program to learn and achieve mor
example_2
- 函数逼近,首先建立模型，使用径向基神经网络对被控对象进行逼近，希望都能到满意的效果-dasj sdij sdjosd asd
2
- 是关于神经网络的数据分类预测的一个源代码，关于向量机的，采用径向基核函数-Neural network data classification forecast
WSVMcgForClass
- SVM高斯径向基核函数 matlab语言 简单易懂-SVM Radial Basis Function
Related-to-the-net
- 线性网络分析 训练前后bp网络仿真结果分析 最简单的径向基网络 bp网络训练演示 newcf函数的误差、权值情况 比较不同节点时网络训练的误差效果- Linear Linear Network Analysis Network Analysis before and after training bp network simulation results analysis easiest RBF network bp network training demo newcf func
imbanlace_kernel
- 基于径向基核函数的不均衡数据集的极限学习机分类源代码-Based on radial basis function unbalanced datasets Extreme Learning Machine classifier source code
svm
- SVM平台，操作简单、易于使用的通用SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题，提供了线性、多项式、径向基和S 形函数四种常用的核函数供选择。-SVM platform is a simple, easy to use, versatile SVM software package can solve classification problems (including
RBFregression
- 径向基神经网络来实现非线性的函数回归，详细讲解可看<<MATLAB神经网络30个案例分析>>这本书-RBF neural networks to achieve nonlinear regression function, explain in detail to see MATLAB neural network 30 case studies in this book
important2
- 基于聚类的径向基神经网络的设计算法，采用的是K均值聚类。实现函数拟合！-The design algorithm of radial basis function neural network based on clustering, using the K mean clustering. Realize the function fitting!