文件名称:rnnsimv2
介绍说明－－下载内容均来自于网络，请自行研究使用
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.
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.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
rnnsimv2
........\contents.m
........\etract_name.m
........\example1
........\........\rnn_gen_con1.dat
........\........\rnn_gen_log1.m
........\........\rnn_gen_log1.txt
........\........\rnn_gen_net1.m
........\........\rnn_gen_trn1.m
........\........\rnn_gen_tst1.m
........\........\rnn_gen_wts1.mat
........\........\temp_con.dat
........\........\use_rnn_gen1.m
........\example2
........\........\rnn_gen_con2.dat
........\........\rnn_gen_log2.m
........\........\rnn_gen_log2.txt
........\........\rnn_gen_net2.m
........\........\rnn_gen_trn2.m
........\........\rnn_gen_tst2.m
........\........\rnn_gen_wts2.mat
........\........\TEMP_CON.DAT
........\........\use_rnn_gen2.m
........\initialize.m
........\initialize_weights.m
........\load_net_file.m
........\load_trn_file.m
........\load_tst_file.m
........\read_connection_matrix.m
........\readme.txt
........\rnn_gen_test_exact.m
........\rnn_gen_test_iterative.m
........\rnnsimv2.pdf
........\test_rnn_gen.m
........\train_rnn_gen.m
........\vardef.m
........\contents.m
........\etract_name.m
........\example1
........\........\rnn_gen_con1.dat
........\........\rnn_gen_log1.m
........\........\rnn_gen_log1.txt
........\........\rnn_gen_net1.m
........\........\rnn_gen_trn1.m
........\........\rnn_gen_tst1.m
........\........\rnn_gen_wts1.mat
........\........\temp_con.dat
........\........\use_rnn_gen1.m
........\example2
........\........\rnn_gen_con2.dat
........\........\rnn_gen_log2.m
........\........\rnn_gen_log2.txt
........\........\rnn_gen_net2.m
........\........\rnn_gen_trn2.m
........\........\rnn_gen_tst2.m
........\........\rnn_gen_wts2.mat
........\........\TEMP_CON.DAT
........\........\use_rnn_gen2.m
........\initialize.m
........\initialize_weights.m
........\load_net_file.m
........\load_trn_file.m
........\load_tst_file.m
........\read_connection_matrix.m
........\readme.txt
........\rnn_gen_test_exact.m
........\rnn_gen_test_iterative.m
........\rnnsimv2.pdf
........\test_rnn_gen.m
........\train_rnn_gen.m
........\vardef.m