I have 9600 inputs as mention before. And 7000 of them is "-1" and 2600 is "1" then the sum is aprroximate -4k , but the sum sometimes
has different value like -0.7 aprroximate 0 , the reason could be the percentage between "-1" and "1" is 50:50 . I trained 1000 samples ,each sample has 9600 inputs . Inputs and outputs are [-1,1...-1] and[-1,1] , learning rate :0.1, momentum :0.1, alpha : 2, neurons of 1st layer :2 , neurons of 2nd layer : 1

- exsigmoid2.png (6.97 KiB) Viewed 21767 times

- exsigmoid1.png (6.76 KiB) Viewed 21767 times
After that I try to change alpha to 1/4k6 and the errors decrease from 609 to 608 for 1000 iterations .In order to make the error decreasing to 0 , I have to set 600k iterations (I think). To me , it takes a lot of time just for 1000 samples . If someone want to increase the number of samples to 10k or 100k just for simple structure network ( 9600 inputs, 2 outputs, 2 neurons of 1st layer, 1 neuron of 2nd layer), are there any better solutions or better approaches ?