文件名称:40000-Samples-For-4Ch_4---Network
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Random Neural networks for cognitive radio network modelling. training and uation
of the random neural network. main file, connection file, and net file. The parameters of the network will be saved to the weight file-Random Neural networks for cognitive radio network modelling. training and uation
of the random neural network. main file, connection file, and net file. The parameters of the network will be saved to the weight file
of the random neural network. main file, connection file, and net file. The parameters of the network will be saved to the weight file-Random Neural networks for cognitive radio network modelling. training and uation
of the random neural network. main file, connection file, and net file. The parameters of the network will be saved to the weight file
(系统自动生成,下载前可以参看下载内容)
下载文件列表
40000 Samples For 4Ch_4 - Network.fig
40000 Samples For 4Ch_4 - Reward.fig
Binary.m
contents.m
create_fit_net.asv
create_fit_net.m
create_fit_net_variable_noise.m
CreateExtendedTrainingSet.m
CreateNetworkSpectum.m
CreateNetworkSpectum_Channel_0_1.m
CreateNetworkSpectum_Channel_0_1_Ch2withNoise.m
DataFileFor_rnn_gen__con1_4Ch_4.mat
DataFileFor_rnn_gen_con1_10Ch_10.mat
DataFileFor_rnn_gen_con1_10Ch_10_wts.mat
DataFileFor_rnn_gen_con1_10Ch_10_wts_GOodFor_10000.mat
DataFileFor_rnn_gen_con1_10Ch_10_wts_GoodResults.mat
DataFileFor_rnn_gen_con1_10Ch_40.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts_GoodResults.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts_N.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts_N_Ch2.mat
DataFileFor_rnn_gen_con1_2x4Ch_24 .mat
DataFileFor_rnn_gen_con1_4Ch_16.mat
DataFileFor_rnn_gen_con1_4Ch_16_wts.mat
DataFileFor_rnn_gen_con1_4Ch_16_wts_N.mat
DataFileFor_rnn_gen_con1_4Ch_16_wts_N_Ch2.mat
DataFileFor_rnn_gen_con1_4Ch_2.mat
DataFileFor_rnn_gen_con1_4Ch_2_N.mat
DataFileFor_rnn_gen_con1_4Ch_2_wts.mat
DataFileFor_rnn_gen_con1_4Ch_2_wts_N.mat
DataFileFor_rnn_gen_con1_4Ch_24.mat
DataFileFor_rnn_gen_con1_4Ch_24_wts GoodResults.mat
DataFileFor_rnn_gen_con1_4Ch_24_wts.mat
DataFileFor_rnn_gen_con1_4Ch_4.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_2to1.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_GoodResults.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_N.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_N_Ch2.mat
DecideNextChannel.m
error_file.mat
etract_name.m
GetErrorGraph.m
GetInputOutputVec.m
GetInputOutputVec2Input.m
GetNextSlotState.m
GetNextSlotState_forErrGraph.m
HelpMe.mat
initialize.m
initialize_weights.m
InterativeRNNWeightes.m
load_net_file.m
load_trn_file.m
load_tst_file.m
main.m
NN_dataFile.mat
NN_Main.asv
NN_Main.m
read_connection_matrix.m
readme.txt
Reward.m
rnn_gen_con1.dat
rnn_gen_con1_10-1Ch_10.dat
rnn_gen_con1_10-1Ch_40.dat
rnn_gen_con1_10Ch_10.dat
rnn_gen_con1_10Ch_20x10.dat
rnn_gen_con1_10Ch_2x15.dat
rnn_gen_con1_10Ch_40.dat
rnn_gen_con1_2x4Ch_24.dat
rnn_gen_con1_4-1Ch_16.dat
rnn_gen_con1_4-1Ch_24.dat
rnn_gen_con1_4-1Ch_4.dat
rnn_gen_con1_4Ch_16.dat
rnn_gen_con1_4Ch_2.dat
rnn_gen_con1_4Ch_24.dat
rnn_gen_con1_4Ch_3.dat
rnn_gen_con1_4Ch_4.dat
rnn_gen_con1_6.dat
rnn_gen_con1_6_Temp.dat
rnn_gen_con1_Test2.dat
rnn_gen_log1.m
rnn_gen_log1.txt
rnn_gen_net1.m
rnn_gen_test_exact.m
rnn_gen_test_iterative.m
rnn_gen_trn1.m
rnn_gen_tst1.m
RNN_Gen_Weights.mat
rnn_gen_wts1.mat
temp_con.dat
test_rnn_gen.m
testrun.m
train_rnn_gen.m
use_rnn_gen.m
use_rnn_gen1.m
vardef.m
Weights.mat
WS_FTP.LOG
40000 Samples For 4Ch_4 - Reward.fig
Binary.m
contents.m
create_fit_net.asv
create_fit_net.m
create_fit_net_variable_noise.m
CreateExtendedTrainingSet.m
CreateNetworkSpectum.m
CreateNetworkSpectum_Channel_0_1.m
CreateNetworkSpectum_Channel_0_1_Ch2withNoise.m
DataFileFor_rnn_gen__con1_4Ch_4.mat
DataFileFor_rnn_gen_con1_10Ch_10.mat
DataFileFor_rnn_gen_con1_10Ch_10_wts.mat
DataFileFor_rnn_gen_con1_10Ch_10_wts_GOodFor_10000.mat
DataFileFor_rnn_gen_con1_10Ch_10_wts_GoodResults.mat
DataFileFor_rnn_gen_con1_10Ch_40.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts_GoodResults.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts_N.mat
DataFileFor_rnn_gen_con1_10Ch_40_wts_N_Ch2.mat
DataFileFor_rnn_gen_con1_2x4Ch_24 .mat
DataFileFor_rnn_gen_con1_4Ch_16.mat
DataFileFor_rnn_gen_con1_4Ch_16_wts.mat
DataFileFor_rnn_gen_con1_4Ch_16_wts_N.mat
DataFileFor_rnn_gen_con1_4Ch_16_wts_N_Ch2.mat
DataFileFor_rnn_gen_con1_4Ch_2.mat
DataFileFor_rnn_gen_con1_4Ch_2_N.mat
DataFileFor_rnn_gen_con1_4Ch_2_wts.mat
DataFileFor_rnn_gen_con1_4Ch_2_wts_N.mat
DataFileFor_rnn_gen_con1_4Ch_24.mat
DataFileFor_rnn_gen_con1_4Ch_24_wts GoodResults.mat
DataFileFor_rnn_gen_con1_4Ch_24_wts.mat
DataFileFor_rnn_gen_con1_4Ch_4.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_2to1.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_GoodResults.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_N.mat
DataFileFor_rnn_gen_con1_4Ch_4_wts_N_Ch2.mat
DecideNextChannel.m
error_file.mat
etract_name.m
GetErrorGraph.m
GetInputOutputVec.m
GetInputOutputVec2Input.m
GetNextSlotState.m
GetNextSlotState_forErrGraph.m
HelpMe.mat
initialize.m
initialize_weights.m
InterativeRNNWeightes.m
load_net_file.m
load_trn_file.m
load_tst_file.m
main.m
NN_dataFile.mat
NN_Main.asv
NN_Main.m
read_connection_matrix.m
readme.txt
Reward.m
rnn_gen_con1.dat
rnn_gen_con1_10-1Ch_10.dat
rnn_gen_con1_10-1Ch_40.dat
rnn_gen_con1_10Ch_10.dat
rnn_gen_con1_10Ch_20x10.dat
rnn_gen_con1_10Ch_2x15.dat
rnn_gen_con1_10Ch_40.dat
rnn_gen_con1_2x4Ch_24.dat
rnn_gen_con1_4-1Ch_16.dat
rnn_gen_con1_4-1Ch_24.dat
rnn_gen_con1_4-1Ch_4.dat
rnn_gen_con1_4Ch_16.dat
rnn_gen_con1_4Ch_2.dat
rnn_gen_con1_4Ch_24.dat
rnn_gen_con1_4Ch_3.dat
rnn_gen_con1_4Ch_4.dat
rnn_gen_con1_6.dat
rnn_gen_con1_6_Temp.dat
rnn_gen_con1_Test2.dat
rnn_gen_log1.m
rnn_gen_log1.txt
rnn_gen_net1.m
rnn_gen_test_exact.m
rnn_gen_test_iterative.m
rnn_gen_trn1.m
rnn_gen_tst1.m
RNN_Gen_Weights.mat
rnn_gen_wts1.mat
temp_con.dat
test_rnn_gen.m
testrun.m
train_rnn_gen.m
use_rnn_gen.m
use_rnn_gen1.m
vardef.m
Weights.mat
WS_FTP.LOG
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