Description: 实现神经网络中的Adaline的LMS算法，分别对正弦信号和三角波信号识别。-Realize the Adaline neural network of the LMS algorithm, respectively, on the sinusoidal signal and triangular wave signal identification. Platform: |
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Author:李娴 |
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Description: matlab实现ADALINE神经网络和感知器神经网络学习训练及应用-matlab neural network realization of ADALINE neural network learning and perception, training and application of Platform: |
Size: 1024 |
Author:June |
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Description: adaline with bias and problem on adaline algorithm in subject ANN artificial neural intelligence-adaline with bias and problem on adaline algorithm in subject ANN artificial neural intelligence Platform: |
Size: 2048 |
Author:vkesh |
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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: |
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Author:YuWang |
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Description: 实验一：基于LMS算法的“苹果-橘子”分类问题
实验二：基于LMS算法的T-G-F字符识别问题
通过以上两个实验，了解ADALINE网络的结构及计算机制，掌握LMS算法，并会利用该算法来解决简单的模式分类问题。1， 学习ADALINE网络的基本结构及其学习机制，并在Matlab中实现
2， 分别对上述两类分类问题进行实现，并根据实验结果完成实验报告
-Experiment 1: Based on LMS Algorithm Apple- Orange classification issues
Experiment two: TGF-based character recognition problem LMS algorithm
Through the above two experiments to understand the structure and computer network system ADALINE, master LMS algorithm, and will use the algorithms to solve simple pattern classification problem.
1, learn the basic structure and learning mechanism ADALINE network and to achieve in Matlab
2, respectively, for these two types of classification problems were implemented and completed in accordance with the experimental results of test report Platform: |
Size: 40960 |
Author:glm |
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