ann
所属分类：人工智能/神经网络/深度学习
开发工具：matlab
文件大小：144KB
下载次数：79
上传日期：2008-08-18 14:42:31
上 传 者：
fspider
说明： 一个很好用的自适应人工神经网络模型库，包括ADALINE/RBF/多层前向等，另外内含Demo，更易上手
(A good use of adaptive artificial neural network model library, including the ADALINE/RBF/Multi-layer and so on, the other containing the Demo, even易上手)
文件列表:
ann.mdl (183983, 2007-05-09)
anndemo.mdl (23417, 2007-05-09)
contents.m (273, 2007-04-28)
dcsgl2.dll (25600, 2007-04-28)
dcsgl2.mexw32 (28672, 2007-10-17)
demos.m (591, 2007-05-09)
emran8.dll (24064, 2007-04-28)
emran8.mexw32 (24576, 2007-10-17)
info.xml (625, 2007-04-28)
src.z.p (42809, 2007-05-09)
training.zip (45624, 2008-02-13)
vrmult.dll (49152, 2000-10-02)
vrmult.mexw32 (20480, 2007-10-17)
CONTENTS:
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ann.mdl - adaptive neural network library
anndemo.mdl - demo file
contents.m - info file for the Matlab Help and Ver commands
info.xml - info file for the Matlab Start Menu
demos.m - info file for the Matlab Demos Menu
emran8.dll - dll file for grbf network
dcsgl2.dll - dll file for the gdcs network
vrmult.dll - dll file for real matrices multiplication
source.zip - compressed folder containing source code
training - compressed folder containing example on grbf training
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INSTALLATION:
Unzip the file in a folder of choice, usually under the "toolbox" folder
under the Matlab main installation folder.
From Matlab, open the "Set Path" interface from the "File" menu,
and use the "Add with Subfolders" feature to add the new folder
to the matlab path. Then Save and exit the Set Path dialog box.
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HOW TO USE THE LIBRARY:
From matlab, use the command "ann" to open the library, and double click
on the "ann demo" block to open the main demo. This should open a simulink
scheme capable of running "out of the box" with any matlab version from
R11 to R2007a, that is from Matlab 5.3 to 7.4.
To use the library blocks, just drag and drop them into any simulink scheme.
The folder "training" contains instructions on how to train the GRBF network.
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ACKNOWLEDGMENTS:
Partial support for the latter development phases of this library
was given by the NASA Grant # NCC5-685
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G.Campa, West Virginia University, October 2007
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