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文件名称:rnnsimv2

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    2012-11-16
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    302.04kb
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介绍说明--下载内容来自于网络,使用问题请自行百度

RNNSIM v.2 package contains a number of m-files for training and evaluation

of the random neural network. All functions have been thoroughly tested.



After downloading the separate files or the zipped file, make sure that they are

stored or extracted in the directory /rnnsimv2



Below an overview of the files contained in this directory along with a brief descr iption of what

they do. The on-line help facility explains how to call the different functions. You simply write

help <function-name> in the MATLAB command window.



Along with the m-files in this directory you will find a manual for the simulator

in PDF format (rnnsimv2.pdf). Start by printing this out and read the release notes.



Two simple demonstration programs are given to illustrate how most of the functions

work. -RNNSIM v.2 package contains a number of m-files for training and evaluation

of the random neural network. All functions have been thoroughly tested.



After downloading the separate files or the zipped file, make sure that they are

stored or extracted in the directory  /rnnsimv2



Below an overview of the files contained in this directory along with a brief descr iption of what

they do. The on-line help facility explains how to call the different functions. You simply write

help <function-name> in the MATLAB command window.



Along with the m-files in this directory you will find a manual for the simulator

in PDF format (rnnsimv2.pdf). Start by printing this out and read the release notes.



Two simple demonstration programs are given to illustrate how most of the functions

work.



相关搜索: random training matlab

(系统自动生成,下载前可以参看下载内容)

下载文件列表

rnnsimv2/
rnnsimv2/contents.m
rnnsimv2/etract_name.m
rnnsimv2/example1/
rnnsimv2/example1/rnn_gen_con1.dat
rnnsimv2/example1/rnn_gen_log1.m
rnnsimv2/example1/rnn_gen_log1.txt
rnnsimv2/example1/rnn_gen_net1.m
rnnsimv2/example1/rnn_gen_trn1.m
rnnsimv2/example1/rnn_gen_tst1.m
rnnsimv2/example1/rnn_gen_wts1.mat
rnnsimv2/example1/temp_con.dat
rnnsimv2/example1/use_rnn_gen1.m
rnnsimv2/example2/
rnnsimv2/example2/rnn_gen_con2.dat
rnnsimv2/example2/rnn_gen_log2.m
rnnsimv2/example2/rnn_gen_log2.txt
rnnsimv2/example2/rnn_gen_net2.m
rnnsimv2/example2/rnn_gen_trn2.m
rnnsimv2/example2/rnn_gen_tst2.m
rnnsimv2/example2/rnn_gen_wts2.mat
rnnsimv2/example2/TEMP_CON.DAT
rnnsimv2/example2/use_rnn_gen2.m
rnnsimv2/initialize.m
rnnsimv2/initialize_weights.m
rnnsimv2/load_net_file.m
rnnsimv2/load_trn_file.m
rnnsimv2/load_tst_file.m
rnnsimv2/read_connection_matrix.m
rnnsimv2/readme.txt
rnnsimv2/rnn_gen_test_exact.m
rnnsimv2/rnn_gen_test_iterative.m
rnnsimv2/rnnsimv2.pdf
rnnsimv2/test_rnn_gen.m
rnnsimv2/train_rnn_gen.m
rnnsimv2/vardef.m

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