Description: The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring
different adaptation algorithms.~..~
There are 11 blocks that implement basically these 5 kinds of neural networks:
1) Adaptive Linear Network (ADALINE)
2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA)
3) Radial Basis Functions (RBF) Networks
4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN)
5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm
A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included-The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms .~..~ There are 11 blocks that implement basically these five kinds of neural networks : a) Adaptive Linear Network (ADALINE) 2) Multilayer Layer 102206 with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks, 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) and RBF Networks with Piecewise Linear Dynamic Cell Structure (DCS) algorithm A Simulink example regarding the approximation of a scalar nonlinear function of four variables is included Platform: |
Size: 198656 |
Author:叶建槐 |
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Description: 本工具包主要是为对神经网络有兴趣人士提供的一种方便，灵活的学习和研究软件。
JNNT由java语言写成，具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行，无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。
支持反向传播算法(BP),LBG聚类法和径向基网络(RBF)
-This toolkit is for people interested in neural networks has provided a convenient, flexible learning and research software. JNNT by the java language, cross-platform with superior performance. Java applet demo version is more simple to just any machine can run a browser, without installing any large-scale add-on software. Enthusiasts through the internet more convenient remote access to resources. To support the back-propagation algorithm (BP), LBG clustering method and radial basis function network (RBF) Platform: |
Size: 32768 |
Author:林盈 |
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Description: 径向基神经网络Matlab编程，包含4个分厂不错的Matlab程序，读者可以下载运行一下看看。-Radial Basis Function Neural Networks Matlab programming, including 4 branch good Matlab program, readers can download to run about to see. Platform: |
Size: 4096 |
Author:侯杰 |
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Description: 主要是BP神经网络的MATLAB实现程序代码，包括感应器神经网络、线性网络、BP神经网络、径向基函数网络。-Mainly MATLAB BP neural network to achieve the program code, including sensors neural networks, linear network, BP neural network, radial basis function networks Platform: |
Size: 8192 |
Author:方博 |
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Description: matlab神经网络原理与实例精解的matlab源代码，包括matlab快速入门、单层感知器、线性神经网络、BP神经网络、径向基函数网络、自组织竞争神经网络、随机神经网络等各章节源码，是学习神经网络的有力助手，里面包含matlab库函数工具箱的应用，也有手算代码。-matlab neural network theory and examples of fine solution matlab source code, including matlab QuickStart, single sensor, linear neural network, BP neural network, radial basis function network, since each chapter organizing competitive neural networks, Stochastic neural network sourceIt is a powerful assistant learning neural network, which contains the library functions matlab toolbox application, there are hand count code. Platform: |
Size: 608256 |
Author:李强 |
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Description: 自适应神经网络图书馆（Matlab的5.3.1或更高版本）是实现多个自适应神经网络具有不同的自适应算法块的集合。
它主要分布于2001年6月 - 7月詹皮耶罗坎帕（西弗吉尼亚大学）和马里奥·卢卡Fravolini（佩鲁贾大学）。后来改善部分由美国航天局资助NCC5-685支持。
有迹象表明，实施基本上这些种神经网络的块：
自适应线性网络（ADALINE）
多层感知层网络
广义径向基函数网络
动力单元结构（DCS）网络的高斯或圆锥形基函数
此外，包括有关的标量非线性函数逼近的一个Simulink的例子。
最后，该文件包括Training.zip步步instrucions上如何培养GRBF网络和支撑例子。-Adaptive Neural Network Library (version 5.3.1 or higher Matlab' s) is to achieve a plurality of adaptive neural network has a different set of adaptive algorithms block. It is mainly distributed in June 2001- July 詹皮耶罗坎 Pa (West Virginia University) and Mario Luca Fravolini (Perugia University). Later improved in part by the NASA-funded NCC5-685 support. There are indications that the implementation of these types of neural networks basically block: adaptive linear network (ADALINE) multi-layer network-aware generalized radial basis function network power unit structure (DCS) network Gaussian or conical base function addition, including related Examples of scalar nonlinear function approximation of a Simulink. Finally, the document includes a step by step instrucions on how to cultivate GRBF Training.zip network and support examples. Platform: |
Size: 598016 |
Author:YuWang |
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Search - radial basis function neural networks matlab