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