#input normalization
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
#output normalization
1 0
#neurons weights
0
0
0
0
0
0
0
0
-34.1803
-34.4376
-34.1469
-34.9998
-34.179
-34.6976
-34.732
-35
-34.8685
-34.9627
-34.9364
-34.7725
-34.7733
-36.6525
-34.5513
-34.2483
-1.00446
#synapses weights
4.72287
5.57952
14.1881
7.42117
7.22886
4.19528
4.2655
-7.02078
4.51625
5.2968
13.9026
7.18667
7.0265
3.99838
4.06794
-7.2347
4.75113
5.61671
14.2253
7.45097
7.25403
4.21966
4.29005
-6.9938
3.92384
4.1181
12.8881
7.32627
7.90083
4.99559
5.03493
-6.7037
4.57208
5.00705
13.7521
7.71296
7.97641
5.0306
5.10048
-6.41864
4.08517
4.32857
13.1304
7.55635
8.11431
5.21018
5.25656
-6.45771
4.05658
4.30909
13.1066
7.50042
8.037
5.12912
5.17625
-6.52484
3.92096
4.10901
12.8818
7.33773
7.92355
5.02012
5.05889
-6.68669
3.98882
4.17034
12.9667
7.49573
8.12516
5.23008
5.26889
-6.4989
3.93296
4.10057
12.8885
7.41792
8.04956
5.15377
5.19079
-6.58191
3.94784
4.11784
12.9089
7.44297
8.077
5.18188
5.21923
-6.55401
4.04762
4.25112
13.0528
7.55729
8.16896
5.27225
5.31385
-6.4389
4.04714
4.25044
13.0521
7.55685
8.16872
5.27203
5.3136
-6.4393
2.68518
3.01453
11.6509
5.61287
5.87884
2.89824
2.91532
-8.69653
4.2896
4.65272
13.3942
7.47242
7.81375
4.87613
4.93517
-6.64461
4.51996
4.94159
13.6859
7.66751
7.94477
5.00036
5.06824
-6.46176
-4.32916
-3.79774
-4.39663
1.58861
-0.499934
1.48209
1.32544
1.65732
1.91743
1.92087
1.93549
1.82743
1.82852
-0.843675
-0.00714129
-0.42011