Subsequent to {HEAD ~ the gradient propagation}, the weights can be normalized, thereby preventing {TAIL ~ convergence} to a local optimum 
Subsequent to { HEAD ~ the gradient propagation } , the weights can be normalized , thereby preventing { TAIL ~ convergence } to a local optimum
OTH OTH HEAD HEAD HEAD HEAD HEAD HEAD HEAD OTH OTH OTH OTH OTH OTH OTH OTH OTH TAIL TAIL TAIL TAIL TAIL OTH OTH OTH OTH