Description: This program demonstrates some function approximation capabilities of a Radial Basis Function Network.
The user supplies a set of training points which represent some "sample" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the network. Using the training samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting network is then used to approximate the function between the given "sample" points. -This program demonstrates some function a pproximation capabilities of a Radial Basis Fu nction Network. The user supplies a set of train ing points which represent some "sample" point s for some arbitrary curve. Next, the user specifies the number of equally spaced Response centers and the variance for the netwo rk. Using the training samples, the weights multiplying each of the Gaussian ba sis functions arecalculated using the pseudo- inverse (yielding the minimum least-squares s middleware). The resulting network is then used to approximate the function between the given "sa mple "points. Platform: |
Size: 18432 |
Author:陈伟 |
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Description: 可以方便利用训练数据建立径向基函数神经网络并绘制输入-输出网格图。-Can easily make use of training data to establish radial basis function neural network and the mapping of input- output grid. Platform: |
Size: 2048 |
Author:张磊 |
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Description: 神经网络的源码程序，利用c的知识和能用径向基神经网络的功能-Neural network source code procedures, take advantage of the knowledge and use c radial basis function neural network Platform: |
Size: 1024 |
Author:jiangjiuju |
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Description: 针对实际对象数学模型不明确而难以控制的问题,采用人工免疫网络的离散模
型与学习算法,将人工免疫系统与神经网络结构的优势相结合,提出了一种基于人工免疫
网络的模式识别算法,构造了对象识别的人工免疫网络模型.该算法综合了网络节点的定
位与参数调整以及对基函数的平滑因子实施调谐等功能,有效地解决了径向基函数
(RBF)神经网络模式识别的两个阶段任务,使模式识别的精度有较大的改进.采用两个不
同对象函数进行的仿真试验表明,该算法具有快速收敛性与较高的准确性.
-Mathematical model for the actual object is not clear and difficult to control the problem, the use of artificial immune network model and the discrete learning algorithm, artificial immune systems and neural networks combine the advantages of structure, an artificial immune network based on pattern recognition algorithms, Construction of the object identified by artificial immune network model. the algorithm is a combination of network nodes to adjust the position and parameters as well as the basis function implementation of the smoothing factor, tuning and other functions, to effectively solve the Radial Basis Function (RBF) neural network pattern recognition of two phase of the task, so that the accuracy of pattern recognition have greater improvements. the use of two different object functions of the simulation tests show that the algorithm has fast convergence and higher accuracy. Platform: |
Size: 114688 |
Author:杨玉琴 |
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Description: 用径向基函数法实现模式分类，自动选择最佳隐含层书目，并给出差准率和差全率。-Radial basis function method used to achieve pattern classification, automatically select the best hidden layer bibliography, and to the business associate and full-rate differential. Platform: |
Size: 1024 |
Author:曹红丽 |
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Description:
LIBSVM 是台湾大学林智仁 (Chih-Jen Lin) 博士等开发设计的一个操作简单、易于使用、快速有效的通用 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，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation. Platform: |
Size: 518144 |
Author:小潘 |
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Description: 利用网络实现函数逼近
使用的主要函数如下：
NEWRB——设计径向基函数神经网络
SIM——对径向基函数网络进行仿真-Function approximation using the Internet to achieve the main function is as follows: NEWRB- the design of radial basis function neural network SIM- for radial basis function network simulation Platform: |
Size: 1024 |
Author:舒 |
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Description: 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 subclass).
The package also calculates line integrals between two points. Platform: |
Size: 9216 |
Author:辛芳芳 |
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Search - Radial basis function