Residual neural network code implemented now

This is important update from private repo. It enables residual neural network (enabled in nntool). Code automatically uses skip connectiosn from even numbered layers forward if number of neurons for both layers is same. It therefore does mini skips over two layers from the input layer all the way to output layer and implements residual neural network architecture.

Deep learning: for a simple test problem (test_data_residual.sh) neural network can learn the problem with 40 layers in 10 minutes (dense residual neural network with leaky rectifier unit non-linearity), 20 layers residual neural network gives perfect results.